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LIBRARY CD-ROM LAN PERFORMANCE AND

PATRON USE: A COMPUTER

SIMULATION MODEL

DISSERTATION

Presented to the Graduate Council of the

University of North Texas in Partial

Fulfillment of the Requirements

For the Degree of

DOCTOR OF PHILOSOPHY

By

Hong Xia, B.S., M.S,

Denton, Texas

May, 1996

Xia, Hong, Library CD-ROM LAN System Performance and

Patron Use: A Computer Simulation Model. Doctor of

Philosophy (Information Science), May, 1996, 183 pp., 18

tables, 11 illustrations, and 84 bibliography titles.

In this study, a computer simulation model for library

CD-ROM LAN systems was created. Using this model, the

system optimization problems were examined. The simulation

model imitated the process of the actual decision variables

changing their values and generated the corresponding

results. Under a certain system environment, if the values

of decision variables are changing, the system performances

are getting changed also. This study investigated these

relationships with the created model.

The system users' interarrival time, service time, and

other relevant data were collected on randomly selected days

in a university library. For data collection, both of the

observation and the system automatic metering software were

used. According to the collected data, a discrete events

simulation model was created with GPSS/H.

The simulation model was proven valid and accurate by

a pilot test and by the calculation with queuing theory.

Statistical tests were used for data comparison and

analysis. In addition, animation technique was used to show

the simulation process by using Proof Animation. By this

technique, the simulation process was monitored on the

screen.

According to the simulation model output, three

relationship formulas were derived:

(1) The utilization of CD-ROM workstations and the

number of the workstations:

(7=-0.0525+1.132

where U is the utilization, S is the number of the

workstations (S>3).

(2) The CD-ROM users' waiting rate and the number of

workstations:

PFr=0.0014*e 6185/5

where Wr% is the waiting rate, S is the number of

workstations (S>3).

(3) If a user entered the waiting line, the waiting

time in the queue and the number of workstations.

W =0.021*e36-44/5

where Wt is users' waiting time, S is the number of

workstations (S>3).

Based on the collected data, descriptive statistics

were provided. The affection of workstations increasing to

the utilization of librarians was also estimated.

Further studies could separate the whole day into

several segments of time in order to get more accurate

interarrival time distributions for model refining.

Copyright by

Hong Xia

1996

1 1 1

ACKNOWLEDGMENTS

I am indebted to Dr. Donald B. Cleveland, my major

professor, for his helpful guidance and encouragement.

Without his contribution, this research could not have been

successfully completed.

I am also deeply grateful to the other members of my

committee: Dr. Howard Clayton, Dr. Ana. B. Cleveland, Dr.

Kathleen Swigger, and Dr. Raymond von Dran, for their

valuable suggestions, constructive comments, and assistance.

I would like to thank Ms. Pixey Mosley and Mr. Arne

Almquist, librarians in the Willis Library, who provided me

with the system meter recorded data and introduced me to the

library CD-ROM LAN system.

Finally, I wish to express my appreciation to my

daughter, Freda, for her tenderness and love; also, I thank

my wife, Jinyuan, for her patience, encouragement, and

support.

xv

TABLE OF CONTENTS

Page

ACKNOWLEDGMENTS iv

LIST OF TABLES vii

LIST OF ILLUSTRATIONS viii

Chapter

I. INTRODUCTION 1 General background 3

Systems and models Simulation CD-ROM systems in libraries

Problem statement 13 Research questions 13 Purpose of the study 14 Significance of the study 14 Research approach 16 Definitions 18 Study limitation and assumptions 19

II. RELATED LITERATURE REVIEW 20 Development of CD-ROM in libraries 20 Development of CD-ROM LAN 24 Decision making on CD-ROM LAN 27 Operations research in libraries 29 Simulation studies in libraries 32 Special purpose simulation language 37

III. METHODOLOGY 40 Introduction 4 0 Problem Analysis 41

Activities in the system Conceptual model development Logical model development

Building the Simulation Model 4 9 Data collection Data analysis Simulation model development

Model Verification and Validation 59 Summary

v

Chapter Page

IV. ANALYSIS OF SIMULATION RESULT 63 Introduction 63 Terminating Systems 64 Model Generated Data 67

Model multiple runs Model pilot test

Results from the Real System Data 74 System Data vs Model Generated Data 78

Mann-Whitney test to the difference The utilization comparison using the queuing theory

V. DIFFERENT CONFIGURATION EXPERIMENT 85 Different Configurations 86 Confidence Interval Estimation 89 Regression Analysis 91 Utilization of the Librarians 101

VI. SUMMARY AND CONCLUSION 103

APPENDIX A Ill

APPENDIX B 114

APPENDIX C 131

APPENDIX D 160

APPENDIX E 165

APPENDIX F 170

BIBLIOGRAPHY 177

VI

LIST OF TABLES

Table Page

1. Transaction arrivals in the real system 53

2. Interarrival time and service time 54

3. Definitions of the station submodel 57

4. Definitions of the librarian submodel 58

5. Issues in model verification and validation . . . 60

6. CD-ROM stations utilizations and the the differences 68

7. The utilization of the storage LIBRNS and the facilities LIBRN1 and LIBRN2 69

8. Model generated arrivals and service time . . . . 70

9. Average utilizations and 95% of the confidence intervals based on 20 replications 72

10. CD-ROM database connections 76

11. Performance of the waiting line for CD-ROM stations 76

12. Performance of the waiting lines for librarians . 77

13. Performance of the services 78

14. The means comparison of the real system data and the model generated data 79

15. Simulation results of different configurations of the station submodel 87

16. Simulation results of different configurations

of the librarian submodel 88

17. Converted waiting rate for linear regression . . . 96

18. Converted waiting time for linear regression . . . 98

vii

LIST OF ILLUSTRATIONS

Figure Page

1. Systems and models 6

2. Logical model of the library CD-ROM LAN

system 48

3. Utilization and the number of stations 92

4. Regression of utilization on number of

stations 93

5. CD-ROM users' waiting rate 94

6. Converted waiting rate 96

7. Converted linear regression on the waiting

rate 97

8. Users' waiting time in the queue 99

9. The linear regression after conversion 99

10. Converted linear regression on the w;iiting time 100

11. Comparison of the two different librarian assignments 101

Vlll

CHAPTER I

INTRODUCTION

This dissertation deals with the optimization of CD-ROM

system configurations in libraries.

CD-ROM (Compact Disc Read Only Memory) is a recently

developed information storage medium. In the last ten

years, CD-ROM products have entered almost all libraries,

resulting in a considerable amount of change in the storage

and retrieval of information. For example, in many

instances, CD-ROM systems and the CD-ROM disc collections

have replaced manual indexes and card catalogs. Reference

areas that were the domain of print sources are now crowded

with computer terminals and electronic sources. Librarians

who used to show patrons how to use print reference

materials are now asked to teach patrons how to use

electronic sources because much searching has been

transferred from online to CD-ROM searching (Tenopir, 1991).

However, these changes have brought some new problems to

librarians, such as how efficiently do the CD-ROM systems

run? What are the criteria for a CD-ROM system design? How

are users' waiting time and waiting rate affected by the

number of system resources? And what percentage of the time

are the librarians who are involved in this system busy or

1

2

idle? Studies that investigate user information

searching behavior and system optimization play important

roles in solving these problems.

One way to investigate these problems is to create and

run a computer simulation model of a library CD-ROM system.

Simulation models can be used to experiment with alternative

designs or policies and suggest the answers for "what if"

questions for a system. Consequently, simulation models can

be a useful tool for librarians.

Everyday operations in a library can be modeled with

basic events that involve classical queuing variables.

These events all of which pertain to the user's interaction

with the library CD-ROM systems are arrival, conducting a

search, and leaving. During their searching, the users may

need a librarian's help. The users' searching activities or

behavior may be related to the databases provided by the CD-

ROM system. These events take place at discrete points in

time. So, the whole system can be considered as a discrete

queuing system. Computer simulation is a useful tool for

building a model of this system.

Such a computer simulation model can generate data

showing how the system state is affected by changing the

decision variables, such as how the users' average waiting

time is affected by changing the number of workstations.

Computer simulation is a process of imitating a real

system operation with computer programs. It is a powerful

3

tool for creating a practical model for a system based on

stochastic data. It is an efficient method for studying the

operating behavior of a system over time. Simulation

methods are especially useful in a situation where other

techniques are difficult or too expensive to implement.

Some simulation studies have been done in the field of

library and information science, but there is still

opportunities available for more studies, and unfortunately,

most previous studies were designed by people outside the

field and have tended to solve unrealistic problems or give

complex solutions to trivial problems. For the most part,

these were pure mathematical models and they were not

generally developed and explained by the professionals in

the library field (Main, 1992). In this dissertation, a

practical computer simulation model for library CD-ROM

systems was designed. Patron use and system performance

problems encountered during regular operation were

investigated to provide a tool for designing optimum system

configuration of CD-ROM devices in a library.

General Background

Systems and Models

The use of models to study problems goes back into

antiquity and has been a major technique of many

disciplines. In modern times, model building has become a

sophisticated art as well as a science and continues to be

4

applied to numerous human activities.

In the real world, a set of objects can be called a

system if it has the following properties:

(1) The objects can be observed as entities.

(2) The entities are measurable, or have

quantitatively measurable attributes.

(3) The entities are systematic and the relations

between the quantitative attributes can be observed

(Osborne, M. R. and Watts, R. 0., 1977).

Accordingly, a system can be described as a group of

objects that are joined together in some regular interaction

or interdependence toward the accomplishment of some

purpose. A system is often affected by changes occurring

outside of itself. Such changes are said to occur in the

system environment. In modelling systems, it is necessary

to decide on the boundary between the system and its

environment (Banks and Carson, 1984, p.6). The concept of

system makes the object of a study tangible and measurable.

According to Banks and Carson (1984, p.9), a model can

be defined as a representation of a system for the purpose

of studying the system. Thus, we may regard a model as a

functional description of a system or a real world procedure

to make it easier for an analyst to study the system. The

main goals of modelling are the interpretation and

understanding of the fundamental structure of a complex

system and the use of the model to predict either future

5

events that may occur in the system or additional properties

of the system.

To create a model for a system successfully, certain

basic requirements for a model should be met. An effective

model must reflect three properties of the system:

(1) The model should generally be derived from the

original system by a process involving simplification,

idealization, and approximation.

(2) The model has quantitatively measurable attributes

that can be classified as input variables, parametric or

controllable variables, and output variables.

(3) The model has functional relations between the

several quantitative attributes or variables. These

relations should be represented clearly and logically.

The purpose of a model is to test some hypothesis based

on the functional relations between the quantitative

attributes or variables of the system, and/or to give an

overall picture of the system in general.

If a good model for a complex system is created, the

mechanism of the system's operation can be better

understood. A system manager can predict the changes in the

system due to changes in the system input variables, thus

optimizing the system's performance.

The Classification of Models

According to the researcher's point of view, models can

be classified in different ways. Banks and Carson (1984)

divided models into two general categories: physical scale

models and mathematical models. The relationship between

system and model can be represented by the figure 1.

System

It consists of entities. It is measurable. It is systematic.

Model

A functional description of a system or a real world procedure.

Physical Scale Model

A physical reduction of a system.

Mathematical Model

A mathematical repre-sentation or abstrac-tion of a system.

Figure 1. Systems and Models

(1) Physical scale models.

These model building processes concentrate on the

physical scale reduction for a complex study object system.

For example, a small library that has the same components,

organization, and objectives as a large library could be

7

considered as a model of the large library. The problems

occurring in the large library might be easier to manipulate

in the small library environment but still reflect the same

characteristics as the large library. The result of a study

from the small library could be used to predict the changes

that would happen in the large library.

(2) Mathematical models.

Mathematical models apply symbolic notations, logical

manipulative processes, numerical data, or formulas and

equations in order to abstract or represent a system. One

significant characteristic of a mathematical model is that

numerical methods are involved during the model building.

The system become easy to study with mathematical methods or

logical reasoning, and for this reason, mathematical models

are the most widely used in science and technology.

Using mathematical models, each part of the object

system is represented by mathematical variables. Usually,

to create these models, stochastic or random theory is

involved. Statistical methods are widely used too. The

major attributes of the system are identified with

parameters or variables entering the mathematical equations.

The solutions from the analytical models represent the

predictions and interpretation for the system.

During the building process of a mathematical, logical

reasoning is often used. Using this method, one represents

the system by a sequence of discrete events or logical

8

blocks, each of them indicating a functional relevant part

of the system. The blocks provide the components of the

system and the logical relations among these components.

Logical methods are usually used to show the whole picture

of the system in general and the relationship among the

components in order to provided logical basis for the

further mathematical abstraction.

Simulation Models

A simulation model is a particular type of mathematical

model of a system (Banks and Carson, 1984, p.10). A

simulation model is created by techniques based on

statistics and a set of assumptions of the real system. The

model can be used to investigate certain "what if" questions

about the real system. The potential changes to the system

can first be simulated in order to predict their impact on

system performance. Simulation modelling can be used both

as an analytic tool for predicting the effect of changes to

an existing system, and as a design tool to predict the

performance of a new system under difference conditions.

Simulation is a modeling technique used to imitate the

operations of a system in the real world. The basic idea of

simulation is to represent a complex system with a simple

system that has the same properties as the original one but

is easier to study.

According to simulation theory, simulation procedures

can be considered as a function of time. Thus, the main

9

purpose of simulation is to allow observation of a

particular system over time. From this standpoint, there

are two distinct types of simulation for different kind of

system: (1) discrete-event system simulation, and (2)

continuous-event system simulation.

A discrete-event system is one in which the events

occur at discrete time points. In discrete-event system

simulation, observations are gathered only at selected

points in time when certain changes take place in the

system. In a continuous-event system, the events occur

continuously over time. The continuous-event system

simulation requires that observations be collected

continuously in time.

As an example of discrete-event system, consider a

library check-out service system. Changes in the status of

the system will occur only when a patron either arrives or

completes the service. At these two instances, measures

such as queue length and waiting time in the facility will

be affected. At all other points in time these measures

remain either unchanged or not ready for data collection.

For this reason, a researcher needs to observe the system

only at selected discrete points in time. This is an

example of discrete event system.

On the other hand, for the electrical power consumption

in an information center, changes are taking place on a

continuous basis and this system must be monitored

10

continuously. Such a system is an example of a continuous

event system.

Often, it is difficult or impractical to monitor a

system continuously in a simulation process. In these

situations, a continuous simulation can be conducted by

recording observations at very small intervals in time.

In recent decades, computer technology has been

developing very fast. Computers save analysts from having

to do the complex calculation required in a simulation

procedure. Researchers can design a computer program to

simulate a procedure that occurs in the real system. In

this case, the computer program can be considered as a

manifestation of a mathematical model and the modelling

process is called computer simulation.

Computer simulation developed as computer technology

developed. In order to do simulation efficiently, some

special programming languages for computer simulation were

developed, such as GPSS, SIMSCRIPT II, SIMAN, and SIMULA.

Use of these languages make simulation programming much

easier than employing general purpose languages such as

FORTRAN and more powerful. Furthermore, artificial

intelligence theory opened another door for bringing

simulation procedures closer to the real world.

CD-ROM Systems in Libraries

After some ten years of development, CD-ROM information

systems have been become well established in libraries and

11

other information service agencies. The operation of CD-ROM

systems is based on optical information storage technology,

laser technology, and digital information processing

technology. Each CD-ROM disk can carry at least 550MB of

digital data. This is equal to the text content of 150,000

printed pages or 1200 5.25 inch floppy disks (Laob, 1986).

The idea of optical information storage technology

appeared in the late 1920's. The first prototype using

laser beams for recording and playback was demonstrated by

Phillips in 1972 (Gale, 1984; Kittle and Wood, 1993).

Afterwards, this technology was used to produce audio discs.

Then, the idea was extended to text information storage and

retrieval. The CD-ROM disk, which has the same size as an

audio CD, emerged in 1984. The first prototype CD-ROM

system was demonstrated at the 1984 Conference of the

American Library Association. This prototype system was

called MARVLS (MARC and REMARC Videodisc Library System) and

was produced by International Thomson, Inc. (Gale, 1984).

The appearance of CD-ROM technology provided an

alternative method for information storage and retrieval.

Since entering the library market, CD-ROM databases have

been keeping a high growth percentage. In 1993, there were

4,422 different CD-ROM titles. This number represented a

3 8% increase over 1992, although the growth rate has been

slowing down over the past several years (65% in 91-92, 90%

in 90-91, and 100% in 89-90). The total number of

12

commercial CD-ROM titles available in 1994 reached about

8500 (Nicholls, Sutherland, and Julien, 1994). Thus the

total number of CD-ROM databases now seems to have exceeded

the number of those available online.

Because of advances in CD-ROM technology, using CD-ROM

has become the cheapest way for information storage and

delivery. Wiedemer and Boelio (1995) compared various

information media and pointed out this conclusion. The cost

of delivering 1 MB information, by online, would be $17; by

print paper, $3.50; by CD-ROM, only $0.0024. The lowest

cost for information delivery is one reason of the fast

development of CD-ROMs.

In the first few years, CD-ROM stations were isolated

machines in libraries. One computer had one CD-ROM drive

and used one database. If the user wanted to change

databases, the CD-ROM disk had to be changed. Users

couldn't share the same database at the same time since the

workstations were isolated. Sometimes, the users had to

wait in line for a particular database while other stations

were idle. These stand-alone CD-ROM stations were not

economical nor practical. As a result, the idea of CD-ROM

networks was introduced. Using a CD-ROM network, a number

of CD-ROM drives are put together and controlled by the

network server. From any station on the network the user

can access CD-ROM drives mounted in the server computer in

the same manner as they access local drives, and the CD-ROM

13

drives in the server can be made accessible by multiple

users simultaneously. Now, many CD-ROM database vendors

have agreed to license multiple users access (Perratore,

1991).

Usually, CD-ROM networks use local area network

technology, so they are called CD-ROM LANs. CD-ROM LANs

solved database sharing and time sharing problems and became

a standard configuration.

Problem Statement

CD-ROM LAN systems have been implemented extensively in

libraries. A basic decision-making problem in the design

and management of such system is how to best configure these

systems; how should workstations and librarians be best

organized?

Research Questions

The following questions were addressed in this study.

1. As the basis of a simulation study, what are the

necessary data that must be collected from a real system,

and the distributions that can be used to build the

simulation model?

2. How does the number of workstations affect whether

or not users wait and the waiting time if they enter a

queue? How does the number of librarians affect whether or

not users wait and the waiting time if they enter a queue?

14

3. With a certain system configuration, what is the

utilization of the workstations? What is the utilization of

the librarians?

4. How do the number of workstations and the number of

librarians in the system affect the utilization of two

system resources? Can the value of these utilizations be

predicted when the number of these resources change?

5. On average, during each CD-ROM search, how many

databases are accessed by a user?

6. What is the minimum requirement for the system

resources to keep the system running smoothly?

Necessary data were collected, analyzed, and a

simulation model was designed and tested in order to answer

these questions.

Purpose of the Study

The purpose of this dissertation was to build a

computer simulation model for a library CD-ROM LAN system.

The simulation model and the results of this study should

help librarians and system designers make decisions and gain

a greater degree of understanding of a CD-ROM system's

utilization performance in order to optimize the system in a

particular library.

Significance of the Study

A CD-ROM LAN is an economical and practical way to

15

implement CD-ROM systems for public users.

Under certain system environments, there is a series of

decision making problems for CD-ROM LAN system management

and design. How to maintain the best balance between user

demands for the equipments and the library's budget is one

of the examples. In an existing system, it is impractical

to collect data directly by changing the CD-ROM LAN system

configuration in a trial-and-error manner, such as varying

the number of workstations, the number of databases, etc..

This study attempted to provide a method to overcome

the difficulty by using a computer simulation model. This

computer simulation model imitated the changing of decision

variables and generated the corresponding results. This

study investigated the relationship of the number of the

system resources and the utilization, the relationship of

the users' waiting rate and the number of the system

resources, and the system's performance optimization. In

addition, it compared the difference of the system data and

the computer simulation model generated data.

Since there have been very few practical simulation

studies in the library and information science field, this

study provided not only a model for a CD-ROM LAN system, but

also an example of a computer simulation application that

could be appropriate for the library and information science

area in general. In addition, animation technique were used

to show the simulation process. Proof Animation release 1.1

16

was chosen as the animation software, which was driven by

the model output data. There was no report found in the

literature that this technique had ever been used to study

library CD-ROM LAN systems. Therefore, this study provided

an important contribution to the body of knowledge of

library CD-ROM LAN systems.

Research Approach

In a library, there are wide variations in CD-ROM

system users' arriving behavior. For example, in a

university library, users often use CD-ROM stations at the

end of a semester to finish their term assignments. At the

beginning of a semester, there are fewer CD-ROM users than

at the end of a semester. In addition, during a given day

or week, the users' interarrival time also varies.

In order to make the simulation model more valid for

steady-state behavior, the data collection time covered four

days, randomly selected over a two week period in middle of

the spring semester of 1995. In order to collect data that

truly represented system behavior, the whole days'

activities were recorded from the time the library opened

until it closed. In this way, one uncontrolled source of

variation, traffic between busy periods and non-busy

periods, was eliminated.

This study consists of five basic steps:

(1) Data collection.

17

- Collect data about CD-ROM users' interarrival time

and variation in the frequency with which the users

come to use the CD-ROM stations.

- Collect data on users' need of librarian's help; the

frequency distribution of the help time.

- Collect data on the librarians' reference and

telephone answering activities.

- Collect data on the CD-ROM database connections by

the system metering software.

These data were used not only for the simulation model

building but also for the descriptive statistics analysis.

(2) Model building.

- Create a simulation model based on the statistics of

collected data.

- Develop the program code with a simulation language,

and make sure the model is valid and accurate.

(3) Pilot test.

Check the model validation and verification.

(4) Different Configuration Experiment.

Run the simulation model with variations in the CD-ROM

system decision variables.

(5) Output Data Analysis. Analyze the collected data

with descriptive statistics, and compare them with output

from the model to make sure the model generated data are

reliable enough to be used in further study. Analyze how

CD-ROM LAN decision variables affect the patron use and the

18

system utilization.

Definitions

Animation: A computer technology to show the

simulation process with pictures on the monitor base on the

output data of the simulation model.

CD-ROM: Compact disc read only memory.

CD-ROM LAN: A local area network that connects and

allows workstations to access CD-ROM drives on other

computers (or CD-ROM server) on the same network

simultaneously.

LAN (Local Area Network): A local area network (LAN)

is a computer network that connects two or more

microcomputers within a limited geographical area, such as a

building or a department. There are three different network

topologies used on LAN. They are bus, ring, and star. The

purpose of a LAN is usually to share hardware, software,

data or information, and other utilities.

Librarian: The reference librarian or library graduate

assistant who helps the users to perform CD-ROM searching.

Library CD-ROM LAN User: A library patron who uses the

CD-ROM LAN in the library. The remote users are excluded.

Patron use: The patron's physical use of the system.

Simulation model: A computer program which simulates

the running of a real system. It is developed according to

the system logical model. It is also referred to as the

19

computer model.

System resources: The entities that provide service in

the system.

Utilization: The ratio of the system resources' busy

time to the total available time.

Waiting rate: The ratio of the number of users who have

waited in a queue to the number of all users.

Workstation: A microcomputer on a computer network or

a LAN which does local processing.

Study Limitations and Assumptions

The computer simulation model was based on the "steady-

state" performance of the CD-ROM LAN at the University of

North Texas during the regular semester in an academic year.

In order to simplify the problem, this study was concerned

only with the CD-ROM stations located in the reference area

of the Willis Library.

CHAPTER II

RELATED LITERATURE REVIEW

In this chapter, a review of the literature consists of

four parts. The first part introduces the appearance and

the development of CD-ROMs in libraries. In the second

part, the CD-ROM LAN system development, the decision making

problems, and the relevant studies are discussed. In the

third part, the operations research studies in the library

and information science field are briefly reviewed. In the

last part, previous studies on simulation models, methods,

and relevant problems in the library and information science

field are reviewed and discussed. Generally, the whole

chapter provides background review and discussion on the

relevant studies.

The Development of CD-ROM Systems in Libraries

The earliest research articles on CD-ROM systems used

in libraries appeared in the mid 1980s. The subject

heading, CD-ROM, first appeared in the 1985 volume of

Library Literature. The research papers on CD-ROM system

during the early years were mainly concerned with the

introduction of systems and products, CD-ROM system basics

and background, historical development, the

20

21

implementation in libraries, and the relationships with

online searching (Gale, 1984; Murphy, 1985) . These early-

papers pointed out that optical storage technology provided

a new dimension in information access and predicted that

over the next few years the capabilities of CD-ROM

technology could revolutionize our ability to access

information. CD-ROM systems would provide a cost effective

alternative to online searching by permitting entire online

databases to be distributed for local use. Two years after

the appearance of CD-ROM technology, in 1986, Microsoft

Press published a compilation of articles, CD ROM: The New

Papyrus, which gave an overall review in CD-ROM system

technology, products, and applications (Lamber and

Ropiequet, 1986).

During the early years of CD-ROM usage, it was unclear

whether or not the users could perform CD-ROM searches

easily. In 1987, the Albert R. Mann Library of Cornell

University addressed this problem by conducting an

experiment using SilverPlatter ERIC. This study suggested

that users' computer experience was an advantage but not

necessarily in CD-ROM searching. By using CD-ROM systems,

the users not only could save time but also could find

references they would not have found using the printed

indexes (Stewart and Olsen, 1988). In addition, according

to another study, the users believed that CD-ROMs were

easier to use than printed sources (Salomon, 1988). CD-ROMs

22

don't require the users to have computer knowledge or

experience, and in general, there is no computer fear for

users to do a CD-ROM search. In general, CD-ROMs let users

feel more comfortable than when using printed materials.

These positive results supported CD-ROM system installation

in libraries.

In the late 1980s, it was reported that CD-ROM products

had undergone a significant development. At that time,

there were more than 1300 different CD-ROM titles on the

market. The second generation of CD-ROM drives demonstrated

enhanced speed of access and some newly designed relevant

equipment (Herther, 1988). These developments suggested

that the continuing growth of CD-ROM technology could be

safely expected, even though there still existed some

suspicions that CD-ROM was not a new papyrus but rather

merely a passing fad (Simmons, 1989). After several years

of development, SilverPlatter, H. W. Wilson, and The Library

Corporation had become big vendors of CD-ROM products in the

library market place. The CD-ROM products in North America

were divided into two parts: one for processing activities,

the other for accessing databases and library and

information collections (Nelson and Desmarais, 1989) . Now,

this division seems to continue, because CD-ROMs for

individual user entertainment or education is becoming

another group of products.

CD-ROM technology has been successfully established in

23

the information world. As a medium of information storage

and retrieval, CD-ROM products have increased rapidly in the

past few years. One review paper said, "in the 1993, the

total number of commercially available CD-ROM titles have

increased more than 1,000 and reached to 5,500 titles." The

author estimated that the actual number of commercial CD-ROM

titles could exceed 8,000 (Nicholls and Ensor, 1994). The

rapid development and the plenty application of CD-ROMs

behooves librarians to pay more attention to CD-ROM systems

management and user behavior study because CD-ROMs have

become a necessary component for a library.

Since the emergence of CD-ROM technology, libraries

have continued to be the primary consumers of the products.

CD-ROM systems not only provide users with bibliographic

information but also give users multimedia information and

full-text information. With CD-ROM systems development in

libraries, both the lives of librarians and library patrons

have been changed. CD-ROM products have changed the life

and the work day of the reference librarian in many ways,

and with tremendous consequences (Thornburg, 1992).

Librarians not only have to maintain the equipment and

become familiar with the use of the databases, but they also

have to get familiar with the computer systems in general.

Library patrons' information demands are stimulated by

the installation of CD-ROM stations. Searching activities

in libraries have increased with the installation of these

24

systems. Anders and Jackson (1988) reported the impact of

CD-ROM databases on the online searching program at the

Evans Library at Texas A & M University. User demand at the

library far outstripped the capacity. More than a hundred

people tried to use the CD-ROM workstations every day, but

only 25 appointment time slots were available for the users.

Facing this kind of situation, it is necessary for

librarians to give sophisticated consideration to several

factors before making decisions concerning CD-ROM system

design and the applications.

The Development of CD-ROM LAN

Over the years CD-ROM products have overcome a number

of defects. In the early years, librarians pointed out such

shortcomings as expensive prices, slow running,

inconvenience, single drives, and the problem of exchanging

discs. At one point the idea of a jukebox was proposed

(Murphy, 1985). A jukebox can hold several CD-ROM discs and

users don't have to change discs when they select different

databases. This arrangement has limitations, however, since

several discs are put in one jukebox and only one

workstation is allowed to access it, the user-waiting

problem becomes worse.

As computer networks developed, Local Area Network

(LAN) technology was adapted by many CD-ROM systems. The

trials of networking CD-ROM stations started in the late

25

1980s. Vine, a British journal, reported in 1988 that an

experimental work undertook by the Polytechnic of Central

London Library made service available that a CD-ROM drive

could be accessed over a computer network. In recent years,

networking CD-ROM stations has become a hot topic in the

information field. Studies include CD-ROM LAN design and

installation, the expanding of CD-ROM LAN by linking it with

the campus wide area networks (WAN), and the linking of CD-

ROM LAN with the Internet system. CD-ROM LAN will improve

CD-ROM services by providing shared, multi-user,

simultaneous access to the databases, as well as connection

with other networks.

Leggott (1991) gave reasons for connecting CD-ROM

stations by LAN. Except for the multi-user sharing of the

databases, CD-ROM LAN could increase data integrity,

increase system security, increase productivity, and allow

remote access.

Nelson (1992) pointed out some pros and cons of CD-ROM

networks. Some drawbacks of networks were the cost of the

network connection, the increase in staff working time,

additional database charges by CD-ROM vendors, and

uncertainty of future need. To implement CD-ROM LAN,

librarians have to pay attention to the copyrighting and

licensing of CD-ROM products. Librarians should devote

attention to investigating copyright protection and to the

leasing of licensing agreements for individual CD-ROM

26

products which they desire to network. Each individual CD-

ROM product may have its own licensing agreement which will

govern how buyers may use that product, and whether or not

they may put it on a network (Nissley, 1992). Networking

CD-ROM stations is logical and technically possible, but

that doesn't necessarily make it legal (Thompson and

Maxwell, 1990) .

In general, if a library would like to install a CD-ROM

LAN, several problems need to be considered by the

librarian: cost of the equipment, licenses of the purchased

databases, LAN maintenance, network security, network

commands design, indexes and references in the network,

support, databases updates, and physical access (Kester,

1993) .

Currently, there are five basic ways to network CD-ROM

drives. They are distinguished by the location of the CD-

ROM drive, either in the server room or out in the

workgroup. These five CD-ROM network architectures are: (1)

internal standalone CD-ROM drives, (2) peer to peer access,

(3) file server extensions (4) plug'n play CD-ROM mini-

servers, and (5) CD-ROM servers. The factors to consider

when determining the best architecture for a particular

situation include cost, performance, reliability, management

capabilities, and security. Brainard (1995) mentioned these

five different CD-ROM network architectures and pointed out

the advantages and disadvantages respectively.

27

Installing CD-ROM LAN in libraries will bring some new

challenges. These challenges include retraining the staff

and users, studying users information seeking behavior, and

conducting special training classes. It can be predicted

that, in the next few years, the development in CD-ROM LAN

will be continue to develop (Kittle and Wood, 1993; Kittle

and Abella, 1993).

Decision Making on CD-ROM LAN

In a library CD-ROM LAN system design, like any other

system design process, there are great deal of decision

making problems and different approaching ideas. For

example, there are two different design approaches for the

CD-ROM systems. One is to centralize; the other is to

decentralize. A centralized design uses one network to

connect all network CD-ROM drives and workstations together

at one location. A decentralized design separates the CD-

ROMs and workstations into different groups or clusters and

establishes several LANs according to subject areas (Au and

Borisovets, 1990).

There are many factors to be considered for a LAN

design project in a library (Marks and Nielsen, 1991) . For

example, how many network users will there be? This factor

directly relates to how many workstations will be installed

on the network. One objective of networking CD-ROM

workstations is reducing the users' waiting time. In stand-

28

alone CD-ROM systems, users have to wait to use a particular

database since the individual databases cannot be accessed

at the same time. For example, Lewis and Plum (1992)

reported that some CD-ROM databases were in use nearly 70%

of the time that the library was open. "The lines grew

longer and users could not gain access to the sources they

needed. We had to provide multiple access to heavily used

products and to better utilize workstations. The obvious

solution to these problems is a CD-ROM LAN." The designed

LAN should relieve the heavy use problem. However, the LAN

designer must make correct decisions on how many

workstations are operational.

Another factor is how many databases will be run on the

CD-ROM LAN. Logically, the more databases installed on the

network the longer time the users will spend at the

workstations since the users tend to search more resources.

Haynes (1993) suggested that installing too many full text

databases should be avoided on a small LAN.

It appears that there should be some relationships such

as the users satisfaction and the number of workstations,

the number of databases on a network and the users'

searching time, and the number of installed databases and

average number of accessed databases for each searching

task. Unfortunately, according to Haynes (1993), no

research has been conducted to tell us the optimum solutions

in estimating the needed number of computer workstations.

29

Presently, determining the correct number of workstations

for a fixed number of databases mainly depends on the

librarian's intuition.

Location of CD-ROM LAN workstations in a library is

important. Many libraries locate them in the reference

area. With this arrangement, the reference librarians are

available to answer questions and to evaluate the user

response to the CD-ROM products. Reference librarians are

kept busy answering search questions, suggesting appropriate

subject headings, and solving equipment problems while at

the same time they are providing the traditional reference

service to other library patrons (Glitz and Yokote, 1990).

Baycroft (1990) pointed out that effective allocation

of library resources to support the growth and maintenance

of the public access workstations would require a strong and

innovative commitment on the part of library management.

The author suggested that the future will bring about the

integration of CD-ROMs with other information technologies.

Decisions concerning networking technologies will play a

critical role in the success or failure of this integration

process.

Operations Research in Libraries

Model building for a system is a major study area of

operations research. Computer simulation is a powerful tool

for model building. Operations research emerged during

30

World War II. The technique of operations research was

developed to assist the activities of scientists and

mathematicians in formulating and solving problems related

to military operations (Bookstein and Swanson, 1971) .

Operations research studies appeared in library and

information science in the 1950s and became popular in the

1960s according to a bibliography review (Slameka, 1972).

In this field, Morse's book, Liibra.iry Effectiveness: A System

Approach, is a key work (Morse, 1968). In this book, Morse

used probability theory, queuing theory, and Markov process

theory to build models for library activities. Morse

pointed out that library patrons' interarrival time

distributed exponentially if the patrons arrived randomly.

In addition, some application examples and discussions were

given (Morse, 1968, pp. 43-53). Morse's book set a

theoretical base for the further studies.

In 1973, Elton and Vickery defined a model in very

general terms by a mathematical method. A model, in

general, it can be represented as P=f(c,u). The performance

(P) of a system, relative to its objectives, is a function

of its variable attributes - both those under the control of

the decision maker (c), and those not under control (u).

Manipulating the model is a matter of demonstrating how P

will change as c is altered and as u changes. To formulate

a model, it is necessary (I) to identify the relevant

variables c and u, and the range of values that each can

31

take, (ii) to construct a valid operational measure P, and

(iii) to determine the form of the function f (Elton and

Vickery, 1973) .

Model building for a library activity is a main

application of operations research in libraries. Martyn and

Vickery (1970) mentioned that the librarians would find that

a model could be useful. They said that the elements of a

model should include the conditions with which systems

operate; the needs, demands, and requirements of system

users; the alternative modes by which the demands can be

met; and the cost and effectiveness of each mode. Elton and

Vickery (1973) gave attention to the sparse use of

simulation models for prediction and control measures, and

pointed out that the importance of these kinds of

application is not realized by information system managers.

Operations research provides library science

researchers with a powerful tool in theoretical studies in

the field. But it still has some weakness. Bommer (1975)

pointed out four reasons why operations research is not

successful in library and information sciences. The first

reason has to do with too much mathematics. Too much

attention has been devoted to the construction and solution

of mathematical models. The second reason is that too

little attention has been placed on the implementation. A

successful implementation requires a mutual understanding

between the operations researcher and the librarian. The

32

third reason is that too little emphasis has been focused on

the process of operations research itself. Too often

operations research is viewed as a product. The last reason

is that too little attention has been paid to the processing

of strategic problems of library managers. Too often

operations researchers have searched for a problem which is

most conductive to analytical model building, irrespective

of the manager's needs.

Even though operations research has these four

shortcomings in the library and information science field,

scientists still have made considerable progress, especially

in theoretical studies. Losee (1990) published a book, The

Science of Information. In this book, the author summarized

many operations research results and used mathematical tools

to define information and its representation, organization,

retrieval, measurement, and other information activities.

Simulation Studies in Libraries

Computer simulation became a powerful problem solving

technique along with the development of computer hardware

and software. Simulation studies have been applied to

library and information science field for about thirty

years. The 1970s were productive years for this technique

(Main, 1992) .

Computer simulation uses a computer program to model

and study the performance or behavior of a system over time.

33

It is based on a conceptual model of the system which is

abstracted by the researcher according to the properties of

the system. A simulation model is a controlled re-creation

for a real system over time. Simulation is a method that

generates an artificial system to imitate a real situation.

In the library and information science field, most

simulation models were built for information access

services, library management, and circulation activities.

Thomas and Robertson (1975) reported a library system

simulation pilot study by the Aslib. This study used GPSS

language to create the simulation model. It aimed at the

investigation of the practicality of developing and using

simulation models of library operations. The model

simulated the library technical procedures, such as select,

order, receive, accession, classify, catalog, label, shelve,

location, list, lend, recall, bind, replace, and withdraw.

Based on these basic description of a library system, when

certain input was given, the operational statistics would be

produced. This output data was considered as the

representation of the library system performance. Compared

with other simulation projects in libraries, this study was

larger in scale and was an attempt to represent many

different subsystems in one model.

Regazzi and Hersberger (1976) created a simulation

model for library reference desks. The study attempted to

record the extent to which queues develop at a reference

34

desk during peak periods and used a simulation technique to

suggest alternative staffing patterns which could reduce

such queues without dramatically increasing the costs.

Parrott (1988) also gave a simulation model for reference

desks. A library circulation system simulation model was

developed by Shaw (1975). This model simulated different

policies and their affections to book availability based on

the data collected at the Case Western Reserve University.

The last due date for books in any library collection can be

used to analyze the circulation performance. Based on this

method, Trueswell and Turner (1979) created a mathematical

simulation model to describe the circulation activities and

thus obtained the circulation rate curve. In academic

libraries, book reservation is a typical service. Depending

on the size of the patron group, how many copies should be

reserved to satisfy the patrons' demand is a decision making

problem. Baumler and Baumler (1975) created a GPSS/360

model to simulate this policy decision problem.

These model building studies usually are not only for a

model creation but are also used for system evaluation by

running the simulation model on a computer. Bourne and Ford

(1964) used a simulation model to do a cost analysis for

evaluation purposes for large information systems. It is

one of the earliest simulation studies in the library and

information science field. Stephens (1970) reported that

New York State Library at Albany used a computer simulation

35

model with GPSS to evaluate library administration

processes. The author studied the effect of project

personnel changes and increased work loads. Karim (1992)

evaluated the effectiveness of decision making under certain

information environments by simulating the cost/benefit

tradeoff under the different conditions. This study

simulated the information processes of a single hypothetical

decision maker involved in multi-attribute choice decision

making tasks. Shafa (1980) developed a simulation model

with FORTRAN for staffing reference services in university

libraries. The model was used for a general cost effective

test purpose. Main (1989) compared six different library

circulation simulation models. The study attempted to

explain why computer simulation models are not implemented

to any extent in libraries.

Other simulation models were built for imitating

information online searching activities. These kinds of

studies concentrate on training or teaching by simulating

real online searching environments (Armstrong, 1987; Hines,

1985; Palinscar, 1986). These studies usually created a

tutorial system which emulated a real online searching

system, such as DIALOG or OCLC, for teaching or training

purposes.

Stirling (1984) provided an alternative for reducing

costs of online search training by computer simulation. A

program, DIALTWIG, was used to emulate many features of the

36

DIALOG system. Structured search assignments were given to

students to familiarize them with the basic operations of

DIALOG searching. Later, Broadway (1987) discussed the

advantages of using DIALTWIG to teach online searching

classes and described how to download and create a database

by using DIALTWIG.

There have been some computer simulation models for

library networks. Williams (1976) reviewed a library

network simulation experiment that used a computer

simulation technique to design a computer based library

network of six academic libraries in western Pennsylvania.

A choice was made to use simulation to identify cost

effectiveness boundaries and design alternatives. The

simulation incorporated a model of acquisition decisions and

processes, technical processing, circulation and public

service. By changing the values of selected variables over

a given range it was possible to determine the impact of

various usage levels and decision processes on the

cost/benefits of the network. Dubey (1984) provided another

research report on library networks by simulation. This

paper pointed out that the problems in the library

networking environment do not yield to algorithmic

solutions. Because of the large number of interrelated

variables involved, library network problems are best

approached heuristically. A decision support system using

simulation techniques may improve the heuristics, however.

37

Not only on a library network, but in any individual

library, most of the activities are human or social. In

these models, the outcomes are not predetermined completely

(Williams and Pope, 1976, pp.3). Compared with the other

mathematical modeling methods, the computer simulation model

could be better used in dealing with these kinds of model

building problems. Main (1992) suggested that librarians

should look at computer simulation modeling again. This

paper concluded with the idea that computer simulation

modeling has tremendous potential for use with the data

stored in the files of automated library systems and pointed

out that visual simulation or animation technique could be

developed to help librarians solving their problems. In

this paper, Main pointed out the major problems in library

systems computer simulation studies. These problems can be

divided into four categories: research problems were not

defined clearly and not completely, some of the studies

didn't have a clear conceptual framework or a conceptual

model, the system constraints were not be considered

carefully, and lack of the interaction between researchers

and librarians (Main, 1992). Future studies should pay more

attention to these problems if the simulation models are to

become more valid and practical.

Special Purpose Simulation Language

To establish a simulation model, any general purpose

38

programming language can be used, such as FORTRAN, Pascal,

or C. However, since these languages are not particular for

describing simulation process, it requires more programming

skills and a longer time for simulation model building.

Lately, many special purpose simulation languages have

been developed such as GPSS, SIMSCRIPT, and SLAM. They

provide the researchers very powerful tools to code

simulation models. Usually, they are easy to learn and easy

to use, and the model builder doesn't have to be an expert

programmer.

To select a suitable simulation language depends on the

nature of the system to be described. For example, GPSS is

a highly structured transaction oriented simulation

language. It is designed for queuing systems model

building. SIMAN (SIMulation ANalysis) is suitable for

modeling discrete event, continuous event, and combined

continuous/discrete event systems. SIMSCRIPT II.5 and SLAM

are specially designed to facilitate model building, and to

more complex systems model building.

In addition, several selection criteria are suggested

(Hoover, and Perry, 1989): ease of learning, ease of

explanation to non-technical individuals, presenting a

standard for all computers, and need less cost.

GPSS, General Purpose Simulation System, is a

simulation modeling language used to build computer

simulation models for discrete event simulation (Schriber,

39

1993). GPSS is one of the first languages to address

simulation model coding. It was developed by Geoffrey-

Gordon and published in 1961.

GPSS/H is a much enhanced version of GPSS. With

GPSS/H, the simulation models can be developed rapidly and

effectively. GPSS/H uses a process interaction world view,

and the modeler specifies the sequence of events, separated

by lapses in time, which describes the manner in which

"objects" flow through a system. An object in a GPSS/H

model may be a customer, a user, or any other type of

discrete entity. A GPSS/H model resembles the structure of

the logical model of the system. This modeling approach

contributes greatly to the ease and speed of computer model

building (Smith, and Crain, 1993) .

Compared with other simulation languages, GPSS/H is one

of the most general, flexible, and powerful simulation

environments currently available (Smith, and Crain, 1993).

GPSS/H has the advantages of being easy to learn, easy to

use, and is suitable for transaction processing in a queuing

system. This dissertation uses GPSS/H as the coding

language to establish the simulation model.

CHAPTER III

METHODOLOGY

Introduction

This study used simulation to investigate the

relationship between a library CD-ROM LAN system resources,

configuration, and the system performance. In order to

build a simulation model for a real system, several stages

or levels of modeling should be worked through. Starting

with the real system, a conceptual model is formed that

consists of the system elements and events. Through problem

analysis, a logical model is produced that reveals the

logical relationship among the elements and events. A

logical model usually looks like a flow chart. According to

the logical model, a computer simulation model can be

developed with a programming language. Hoover and Ronald

(1989) pointed out that developing a simulation model is an

iterative process with successive refinements at each stage.

This chapter includes three parts: (1) problem analysis,

(2) simulation model building, and (3) the model

verification and validation.

The problem analysis gives a general description of the

characteristics of a library CD-ROM LAN system and the user

activities. In this part, the study objective, the involved

40

41

variables, and the measures of system performance are

defined. All of these form the conceptual model. The

logical model is produced according to the conceptual model.

The latter gives a general logical relationship among the

elements of the conceptual model.

Simulation model building was an important part of this

study. This part included three steps: data collection,

data analysis, and simulation model development. Data

collection was concerned with the process of obtaining data

for model building and refining. The objective in data

analysis was to reorganize the raw data and to get useful

statistics for the model development. Model development

included refining the logical model, coding it with a

programming language, and testing and debugging the code.

In these steps, the model was refined and optimized.

The model verification and validation phase involves

the importance of providing an appropriate and accurate

model for the real system. Model validation and

verification should be considered from the beginning of the

model building and continuous through the whole process.

Problem Analysis

A CD-ROM LAN is a computer local area network which

allows multiple users to retrieve information from the CD-

ROMs simultaneously. Even though the CD-ROM LAN can be

accessed campus wide, most users still go to the library to

42

use the LAN directly. On this LAN, the workstations can be

put at one or several locations. The University of North

Texas Library CD-ROM LAN has two locations. One is in the

Willis Library and the other is in the Science and

Technology Library.

The data used for this study were obtained from the

Willis Library. In this system, the workstations can be

considered as a multiple service channel queuing system.

The users come from an unlimited population. CD-ROM

workstations and reference librarians are considered to be

the service resources. During the users' searching process,

the CD-ROM stations provide users the searching tool and the

reference librarians provide users with help and ready

reference. The whole system can be considered as two

subsystems: the station subsystem deals with user searching

activities at the CD-ROM station; the librarian subsystem

deals with the general questions from the CD-ROM users,

reference questions, and telephone calls.

Suppose there are m workstations and n reference

librarians on the LAN, the whole system can be represented

by an m parallel service channels queuing system, and an n

parallel service channels queuing system.

Activities in the System

A model should represent the real system in a valid and

accurate manner. Analyzing the activities in the system is

the first step for problem analysis and formulation.

43

The activities in a library CD-ROM LAN system can be

considered as following:

The user approaches the system workstation area. If

there is any empty workstation, the user will take one and

start searching. If all workstations are occupied by

others, the user will wait in line or will leave and come

back later. Such behavior is referred to as balking. In

libraries, some users will leave the queue and perform other

activities and come back later rather than wait in line.

During the searching, the user may access one or

several different databases. Just how many databases will

be accessed by a user in one searching task depends on how

many databases are available and how much free time the user

has. In the searching process, if the user doesn't

encounter any problems, the user will finish the task and

leave. If the user has any question, the user will ask a

librarian for help. If the librarian is not busy, the user

will receive the help immediately; otherwise, the user will

wait for his/hers turn in order to get help. Sometimes,

the librarian's service might be interrupted by a telephone

call.

After receiving help, if the user doesn't have any more

problems, the user will finish the searching and then leave;

on the other hand, if the user encounters any new problem,

seeking the librarian's help will be repeated.

Several assumptions should be made.

44

(1) The reference librarian is on duty and only has

two possible options: busy (helping other patrons), and

ready to provide help.

(2) Other than asking for individual instruction

throughout the whole process of searching, users generally

only ask librarians short questions.

Conceptual Model Development

The conceptual model of a system contains the elements

of the real system which should be included in the model.

Building the conceptual model requires the researcher to

identify those elements of the real system that will be

included in the model along with the events that occur in

the system. In addition, all the variables, measurements,

and operation rules should be defined. Based on the problem

analysis, the library CD-ROM LAN system consists of the

following:

(1) Events:

In the station subsystem:

(I) A user arrives at the CD-ROM LAN system area.

(ii) The user selects a CD-ROM workstation.

(iii) The user begins the searching task.

(iv) The user finishes the searching task.

(v) The user departs the system.

In the librarian subsystem:

(I) A CD-ROM user needs librarian's help.

(ii) The CD-ROM user receives the librarian's

45

help.

(iii) A library patron arrives at the help desk

for reference services.

(iv) The patron gets the reference service.

(v) The patron departs the system after the

reference.

(vi) A telephone call arrives at the reference

desk (It has priority to be answered immediately

and the other job will be interrupted).

(vii) A librarian answers the telephone call.

(viii) The librarian finishes the telephone call.

(2) Components of the System.

Entities:

- Library CD-ROM LAN users.

- The CD-ROM workstations on the LAN.

- The reference librarian who helps users.

Resources:

- CD-ROM LAN workstations (nine stations, four

386DX40, four 486SX25, and one 486DX33, are

available from 8:00 a.m. to 12:00 midnight,

weekdays).

- Reference librarians (two librarians are

available from 9:00 a.m. to 10:00 p.m., weekdays).

(3) The Variables of the System.

System Condition Variables:

- CD-ROM users' average interarrival time (it is

46

relevant to the average number of the CD-ROM users

per day).

- The percentage of the users who balk when there

is a waiting line.

- Users' average searching time.

- Total number of times the librarians help the

CD-ROM users per day, on average.

- The average interarrival time of the help

requests from the CD-ROM station users.

- Librarian's average helping time for the CD-ROM

users.

- The average inter-occurrence time of the

reference activities.

- The librarian's average service time for the

reference.

- The average inter-occurrence time of telephone

calls.

- The average service time for answering the

telephone calls.

System State Variable:

- Number of users waiting in line.

- State of the workstations (busy or idle).

- State of the librarian (busy or idle).

Decision Variables:

- Number of Workstations.

- Number of librarians (more workstations need

47

more librarians).

(4) Measurements and Rules.

Measures of Performance:

- Utilization (percentage of the busy time). of

the workstations.

- Utilization of the librarian.

- The probability of a user having to wait in the

queue for using a workstation.

- The probability of a user having to wait in the

queue for librarian's help.

- The average time a user spends in the system.

Operational Rules:

- No switching stations after initial selection.

- No leaving after entering a waiting line in

librarians submodel.

- The queue for using workstations is first-in,

first-out, with no special priority.

- The queue for a librarian's help is first-in,

first-out with special priorities (answering

telephone calls).

(5) Not Included Aspects of the Real System.

- Equipment failures.

- The effect of the network system processing time

and variations that delay the users searching

time.

- Unusual events.

48

user arrives

Would tue Occupy a station and begin searching user like to Enter the queue wait?

r N

User leaves

V J

Conduct reference

Reference patron arrives

Patron leaves

Enter the queue

f ~\ Telephone

1 call arrives )

Get a librarian to answer the call

y r

The librarian finishes the call

J

Is librarian free? .

Problem is solved

Enter the queue

Receives help

Help request is asked by CD-ROM users

Figure 2. Logical Model of the Library CD-ROM LAN System

49

Logical Model Development

According to the conceptual model and the problem

analysis, the logical model can be developed as shown in

figure 2.

A logical model represents the logical relationships

among the events and other elements of the system that have

been identified by the conceptual model. During the logical

model development, the conceptual model can be revised and

refined so that the system can be represented by a more

valid model.

In this model, it can be found that the reference

librarians' activities, such as providing ready reference

and answering telephone calls, are involved in the CD-ROM

LAN system performance.

Building the Simulation Model

In this dissertation, a simulation model refers to a

computer program which simulates the real system. In

building a simulation model, a critical step is to get valid

data. Based on these data and the logical model, the

simulation model was developed using GPSS/H, a simulation

programming language.

Data Collection

Data collection was the foundation for building the

simulation model. The raw data came from two sources. One

was the CD-ROM LAN automatic recorded statistics (recorded

50

by the metering software on the network) provided by the

system librarian. The other source was the data collected

from direct observation.

The recorded data from the system meter provided

information on the total database connections from the nine

stations in the Willis Library. Even though these data

recorded the exact time of the database login and logout,

they were not accurate for this study because many users

left without logging out. So the connection was not logged

out until the system automatic logged out or until logged

out by the next user. In view of this problem, it could be

found that some connections lasted for several hours. Based

on quality control techniques, the unusual or out of control

data should be avoided (Meredith, and Gibbs, 1984), these

wrong data were deleted from the file (e.g. the connections

which were longer than 3 hours). The data recorded by the

system meter could be called database connection time or the

number of connections other than users' connection time or

the number of user connections. They are accurate for the

system analysis and can be used for studying the database

connection's relevant problems but they are not accurate for

providing information on the user's behavior or experience

in the system.

Direct observation recorded a user's arrival pattern,

the user's performance at the workstation, and the

librarian's activities. Key empirical distributions were

51

generated. These included user's interarrival time

distribution, the workstations service time distribution,

and the librarian's other job's inter-occurrence time

distribution. For practical reasons, this study used these

empirical distributions to build a simulation model that

fitted different situations. They were considered as

parameter estimates for this model. If the model were to be

used for another institution, the model parameters would

need to be changed.

The user population for this study was all users of the

CD-ROM LAN workstations and the reference librarians in the

reference area of the Willis Library. The data collection

was conducted on four days randomly chosen from a two-week

span in the middle of the semester (Wednesday, Feb. 22;

Thursday, Feb. 23; Monday, Feb. 27, and Wednesday, March 1).

The whole day's data were collected.

The data collection sheets were used to record the

necessary data (see appendix A). During the design stage of

the data collection sheet, preliminary observations and

related revisions were made in order for the sheet to

provide valid and useful information. A stopwatch was used

to measure time intervals. All of the raw data were entered

in Lotus-123 spreadsheet files and calculated for obtaining

the necessary data for further data analysis and model

building. The calculations were done to two decimal points

(e.g. 6.55 min.).

52

If the observer interfered with a user during the

direct observation period, the user would not act as usual.

To avoid such problems, the observer kept a certain distance

from the users while recording more than one attribute:

the time of a user arrival.

the time at which the searching begins.

the time when the user asks for a librarian's help,

the time when the user begins to receive librarian's

help.

the time when the user ends the librarian's help,

the time that the searching ends.

the time when the librarian starts and ends doing

other jobs (reference and answering telephone calls).

the time spent by the librarian doing other jobs

(reference and answering telephone calls).

any unusual events.

The transactions arrival data collected from the real

system are listed in the table 1.

During the data collection, even though a sign told the

users that the activities would be observed, the users

didn't pay attention to this activity. The observation was

conducted in such a way not to interfere with the user's and

librarian's normal activities.

TABLE 1

Transaction Arrivals in the Real System

53

Date 2-22 2-23 2-27 3-1

Total # of Database Connections 743 691 707 484

Avg. Time/conn.(min.) 8.14 8.04 9 .53 10.78

No. of CD-ROM Users 264 268 309 223

No. in Queue 48 52 57 26

No. of Balks 18 17 21 0

No. of Help Requests 88 92 110 79

No. in Queue 18 16 19 13

No. of Balks 0 0 0 0

No. of Users for Reference. 169 170 140 128

No. in Queue 32 45 28 19

No. of Balks 0 1 0 0

No. of Phone Calls 24 16 22 32

Data Analysis

Data analysis is the preparation for model building.

The first step of data analysis is getting useful statistics

based on the raw data.

54

TABLE 2

Interarrival Time and Service Time

Mixi. Max. Mean Std.Dev.

CD-ROM user interarrival 0.03 27.97 3.41 3.23 time

The service time 0.59 143.6 21.96 16.41

Time between CD-ROM user help 0.2 47.85 8.24 7.35 request

The librarian

service time 0.52 11.85 2.35 1.6

Reference patrons

interarrival time 0.02 29.68 5.09 4.33

Ref. service time 0.28 21.09 2.33 2.02

Telephone calls

interarrival time 0.5 173.73 29.83 31.38

Teleph. call time 0.25 8.01 1.47 1.23 * The numbers in this table are based on the SAS analysis of all the observed data. The average numbers are little bit different from the results calculated day by day, due to decimal numbers rounding error.

In this study, Lotus-123 was used to tabulate collected

data which were then processed with SAS (see appendix B).

The frequency and cumulative frequency distributions of the

user interarrival time, the time between CD-ROM users' help

requests, and searching time were calculated from the raw

input data. These statistics were the basis for building

the simulation model (Table 2).

55

The entire system had 3 queues for different resources.

Queue 1 was for waiting for an available workstation; queue

2 was for CD-ROM users to wait for an available librarian's

help; queue 3 was for waiting for the reference. Balking

occurred in queue 1. If there was a queue for using the

workstations, on average 3 0.6% of the waiting users balked

and probably came back later (number of balk/number in

queue, 56/183=0.306). There was no record of balking in the

queue 2. In queue 3 (for reference), only 1 balking was

observed during the data collection. This balking were

ignored in the simulation model. Therefore, in the station

submodel, balking was considered, but in the librarian

submodel, that behavior was ignored.

According to the data distributions, all the data

pertaining to interarrival and service times appeared to

roughly follow negative exponential distribution. This

implied that the arriving process of CD-ROM users, patrons

for reference, and telephone calls approximately followed

the Poisson process as pointed out by Morse (1968) in his

book. However, since data distribution is stochastic, it

could change when the samples change or other situations

change. To avoid possible errors from the distribution

variation, the empirical distributions were used in the

model building of this study.

In this study, these empirical distributions were

treated as model variables. When the model is used for

56

another system, these values must be replaced by the data

from that system. It makes this model more practical and

closer to the sample data, thus the error could be smaller

for a particular study. In addition, since the empirical

distributions were used to build the simulation model, it

was not important for this study to test whether or not

these distributions fit theoretical ones such as

exponential.

Simulation Model Development

Based on the data analysis and the logical model, the

simulation model was developed with GPSS/H.

GPSS/H is a transaction-based simulation language. The

entities are referred to as transactions. Using GPSS/H, the

simulation process is controlled by the randomly generated

transactions and they go through all the program blocks.

The whole library CD-ROM LAN user system provides two

facilities: CD-ROM stations and reference librarians. In

connection with these facilities, the system has four

different types of transactions: (1) CD-ROM station users,

(2) the help requests by CD-ROM station users, (3) library

patrons who ask for reference, and (4) telephone calls.

The first type of transactions use CD-ROM stations

only, but the other three types of transactions use

reference librarians. In this study, these two facilities

can be considered as independent of each other. Even though

more stations might attract more users and increase the

57

librarians' load, this correlation was not applicable in

this study because the user arrival behavior was considered

as a constant (all interarrival time and the distributions

were decided according to the collected data). Based on

this assumption, during model building, the whole model was

divided into two submodels: station submodel and librarian

submodel.

TABLE 3

Definitions of the Station Submodel

Base Time Unit: 1 minute Terminating Simulation System Running for 960 Minutes

GPSS/H Entity Purpose in Model

Transactions: Transaction stream CD-ROM station

user arrival. Queues:

SYS To model users' time in the system.

LINE To model waiting line for using stations.

Storage: Stations To model 9 CD-ROM

LAN stations.

During the simulation, the transactions were generated

according to whether or not the relevant facilities were

available. There was no transaction when the facility is

unavailable. For example, there was no patron who would

wait at the reference desk when it was closed. The CD-ROM

stations were available from 8:00 a.m. to 12:00 midnight,

and the librarians were available from 9:00 a.m. to 10:00

p.m.. The difference in available time of these two

58

facilities was another reason to separate the whole system

model into two submodels. Table 3 and table 4 show the

definitions for these two submodels.

TABLE 4

Definitions of Librarian Submodel

Base Time Unit: 1 minute Terminating Simulation System Running for 780 Minutes

GPSS/H Entity

Transactions: Transaction stream 1

Transaction stream 2

Transaction stream 3

Queues: LIBHELP

LIBREF HLPCD

HLPREF

Storage: LIBRNS

Facilities: LIBRNl LIBRN2

Purpose in Model

Help requests by CD-ROM users. They will be processed by LIBRNl if LIBRNl is idle; if LIBRNl is busy and LIBRN2 is idle they will be processed by LIBRN2; if both of librarians are busy, they will form a single queue for both librarians.

Library patrons who need reference. They will be processed by LIBRN2 if LIBRN2 is idle; if LIBRN2 is busy and LIBRNl is idle, they will be processed by LIBRNl; if both of librarians are busy, they will form a single queue for both librarians.

Telephone calls. They will be processed by LIBRN2, if LIBRN2 is idle; if LIBRN2 is busy and LIBRNl is idle, they will be processed by LIBRNl; if both librarians are busy, the call will preempt LIBRN2.

The queue for waiting librarian's help of CD-ROM users.

The queue for waiting for reference. To model librarian's service time of

helping CD-ROM users. To model the service time of reference.

To simulate 2 reference librarians.

To simulate librarian 1. To simulate librarian 2.

59

Based on the submodels, two GPSS/H programs were

developed (see appendix C). One represented the using of

CD-ROM stations; another one represented the using of

reference librarians. These two programs were refined

several times for debugging, verification, and validation.

Model Verification and Validation

A simulation model is an abstraction of the real system

being studied. This abstraction should represent the real

system correctly in logic and accurately in representation.

Model verification is the process of determining

whether the model is implemented correctly in the computer

code and whether the input parameters and logical structure

are represented correctly by the code.

Model validation is the process of determining whether

the model is a meaningful and accurate representation of the

real system.

Model verification and validation are very important

and difficult tasks in simulation model development. Hoover

and Perry (1989, p.281) summarized the issues in simulation

model verification and validation (Table 5).

Model validation and verification should not be

regarded as the steps that can be tacked on to the end of a

project. They should begin at the onset of the model

building process and continue throughout the project

(Carson, 1989).

60

TABLE 5

Issues in Model Verification and Validation

Model Verification Validation

Conceptual Model Will the model answer the questions of concern? Does the model contain all relevant elements, events, and relationships?

Logical Model Are events represented correctly? Are the relationships correct? Are the measures correct or appropriate?

Does the model contain all events included in the conceptual model? Does the model contain all the relationships of the conceptual model?

Simulation Model Does the code contain all aspects of the logical model? Any coding errors? Any calculation errors?

Is the simulation model a valid representation of the real system? Can the simulation model duplicate performance of the real system? Does the output have credibility with the decision makers?

Simulation model animation is a good method with which to

show the simulation process. The demonstrations with animated

models are much more stimulating and successful. Once the

model has been animated, those who are unfamiliar with

simulation, but know the real system well, are more likely to

quickly comprehend (Bodtker, Wilson, and Godolphin, 1993).

Using the animation method, the simulation process can be seen

directly. It provides us with a powerful tool with which to

diagnose the model validation and verification.

In order to make the model valid and verified, the

following steps were carried out throughout the study.

61

Model validation:

(1) Discuss and refine the conceptual and logical models

with the system librarians and reference librarians. Make

sure everything in the model structure is correct, logical,

and suitable for the purpose of this study.

(2) Make sure the data are valid. Pay more attention to

data collection and use the control chart technique to detect

an uncontrolled situation.

(3) Use animation techniques (Proof Animation. Release

1.1) to monitor the dynamic model process {see appendix E).

(4) Compare the model output data with sample data from

the real system.

Model verification:

(1) Use structured programming techniques.

(2) Use a pilot test.

(3) Trace the running of the program.

(4) Use the GPSS/H debugger.

(5) Use animation techniques.

Giving a close and thorough examination of model output

for reasonableness is another useful method for model

verification and validation. GPSS/H automatically collects

many standard statistics for the model. GPSS/H makes it

advantageous to do model verification and validation. After

a model is generated, the output is carefully analyzed and is

used for the model refinement.

62

Summary

This chapter presented a general description of the

methodology used for this study. The three steps of problem

analysis, simulation model building, and model verification

and validation were described. According to the conceptual

and logical models, a simulation model was developed with

GPSS/H. The findings with the simulation model are intended

to aid in decision making in the library CD-ROM LAN design.

CHAPTER IV

ANALYSIS OF SIMULATION RESULT

Introduction

Since a GPSS/H simulation model is driven by system

generated random numbers, the model outputs are random

variables. It is difficult to answer questions of a real

system using the values of these random variables. Without

careful analysis, the model outputs make it easy to reach

wrong conclusions.

Corresponding to the nature of the real systems, the

simulation models can be divided into two types: terminating

models and steady-state models. This study uses the

terminating model, since the library has an open time and a

closing time.

A correct simulation model is the basis for further

implementations. This chapter provides the simulation model

output analysis and describes the steps to ensure the output

was correct and reliable for further study.

To investigate the relationship between the CD-ROM LAN

configuration and the performance, the simulation model was

run with various values of the decision variables changing.

The results of the simulation runs provided the data that

63

64

represented the real system performance in different

situations.

Terminating Systems

A discrete event system can be categorized as

terminating or non-terminating according to whether there is

a special event to stop the system running. The simulation

models for these two different kind of systems are called

terminating models and steady-state models respectively

{Banks and Carson, 1984. P.407).

The system in this study is a terminating system. In

the CD-ROMs subsystem, The CD-ROM stations become available

each day at 8:00 a.m. with no user in the system, and close

at midnight. All the users will leave the system at the

closing time. In the librarians subsystem, the librarians

come on duty at 9:00 a.m. with no patrons waiting, and leave

at 10:00 p.m.. Simply put, the system terminating events of

these two subsystems occur at the closing times. Actually,

the librarians will help the last patron until the answer

has been found, even if it is after the closing time.

This terminating system starts with zero transaction in

the system and ends with clearing all transactions in the

system. The whole simulation process from the system starts

to the ends is referred as one run. Each run can be

considered independent and has the same initial condition.

We do not have to be concerned with auto-correlation among

65

the performance measures for each run nor the bias due to

the initial conditions.

According to Banks and Carson (1984, p.421-423), if a

terminating simulation model runs over the time span [0, TE]

and results in n observations Y1# , Yn. It can be

assumed that these observations are independent. The goal

of the simulation is to estimate the expected value of some

performance measurement for the system:

n Y. q=E(J2 —)

i=i n

Suppose the model runs R times with independent random

number streams and the same initial condition. It is

referred as that the model runs R replications. The

estimated mean of each run can be represented as:

nr Y

e = E — r i=i n„

Where r = 1,2,...,R; R is the time of replications,

Yri is the ith observation on replication r, and I =

1, 2 , . . . , nr.

Confidence intervals can be used to estimate the

desired performance measures.

We have:

i K

The variance estimate can be represented as

66

ri A

6(0) =• R

where

A /\

R

R (0 -0)^ R „

So, the standard error is:

©(§)=-?: JR y/R(R-l) ^ r=l

<E§, R x *—s ' r' \2 r=l

R

The approximate 100(l-a)% confidence interval of the

mean 0 can be represented as:

e - W fe(9)s0ie+to/2ifd(e)

with the degree of freedom (f=R-l), the value of ta/2<f is

given by a t distribution table.

The formulas above were used in this study for the

model output analysis.

67

Model Generated Data

Model Multiple Runs

Multiple runs of the simulation model will provide a

group of output data for statistical analysis.

In this study, the data used for the library CD-ROM LAN

configuration experiment were generated by the simulation

model. These model output data were based on the GPSS/H

system's pseudo-random number generator; so, the output can

be regarded as stochastic. To make sure these data were

valid for the study, a check on their consistency had to be

made.

In computer simulation, the estimation of the system

characteristics depends on the random numbers generated by

the model. The variability exists in the estimated values.

To measure the variability or determine the accuracy of the

estimate, multiple runs of the model are necessary.

Model Pilot Test

In simulation studies, the utilizations of the system

resources are usually used to measure how busy the resources

are. Since the utilization value is always between 0 to 1,

it is not expected to have as much absolute variation as

other performance measures. In this study, the

utilizations' values were selected to test the consistency

of the system. Point estimate and interval estimate were

used to describe the output data.

For a simulation study, the higher number of runs, the

68

more accurate is the output data. In this pilot test, there

were 20 repeated runs (see appendix C). Based on these 20

runs, the data were judged to be consistent. Except very-

few runs, the percentage values of the utilization

difference to the mean were less than 10% (Table 6 and Table

7) .

TABLE 6

CD-ROM Stations Utilizations and the Differences

Runs Util. % Diff. from the mean

Runs Util. % Diff. from the mean

1 0.7 0.084 11 0.674 0.043

2 0.645 -0.002 12 0.611 -0.054

3 0.644 -0.003 13 0.664 0.028

4 0.596 -0.077 14 0.658 0.018

5 0.721 0.116 15 0.638 -0.012

6 0.654 0.012 16 0.61 -0.056

7 0.626 -0.031 17 0.619 -0.042

8 0.624 -0.034 18 0.607 -0.060

9 0.707 0.094 19 0.599 -0.073

10 0.664 0.028 20 0.66 0.022

Mean: 0.646

Std. Err: 0.008

Each number of the percentage of difference was

calculated by the difference between each run result and the

average of the 2 0 runs, then was divided by the mean value.

69

Based on the data generated from the pilot test, the

values of utilizations were very consistent. The standard

errors were very small.

TABLE 7

The Utilization of the Storage LIBRNS and the facilities LIBRNl and LIBRN2

Runs LNS Util. % Diff. from the mean

LN1 Util. % Diff. from the mean

L,N2 Util. % Diff. from the mean

1 0.413 0.070 0.378 0.074 0.448 0.067

2 0.453 0.174 0.417 0.185 0.488 0.162

3 0.406 0.052 0.343 -0.026 0.469 0.117

4 0.399 0.034 0.35 -0.006 0.448 0.067

5 0.352 -0.088 0.291 -0.173 0.412 -0.019

6 0.406 0.052 0.345 -0.020 0.467 0.112

7 0.392 0.016 0.364 0.034 0.419 -0.002

8 0.392 0.016 0.369 0.048 0.415 -0.012

9 0.355 -0.080 0.325 -0.077 0.384 -0.086

10 0.395 0.023 0.381 0.082 0.408 -0.029

11 0.357 -0.075 0.342 -0.028 0.372 -0.114

12 0.346 -0.104 0.296 -0.159 0.396 -0.057

13 0.403 0.044 0.368 0.045 0.438 0.043

14 0.37 -0.041 0.361 0.026 0.38 -0.095

15 0.377 -0.023 0.363 0.031 0.39 -0.071

16 0.37 -0.041 0.333 -0.054 0.406 -0.033

17 0.355 -0.080 0.331 -0.060 0.379 -0.098

18 0.387 0.003 0.36 0.023 0.414 -0.014

19 0.379 -0.018 0.352 0.000 0.407 -0.031

20 0.409 0.060 0.364 0.034 0.454 0.081

Mean: 0.386

Mean: 0.352

Mean: 0.420

Std Err: 0.006

Std Err: 0.006

Std Err: 0.007

70

The other simulation output data values of all

replications, such as arrival numbers and the service times,

were listed in table 8.

TABLE 8

Model Generated Arriving and Service Time

CD-ROM Users Help CD-ROM Users

References Answei calls

: Phone

Arr. S. time Arr. S. time Arr. S. time Arr. S. time

1 255 23 .711 89 2.541 141 2.611 22 1.575

2 232 24.022 87 2.693 146 2.891 25 1.988

3 234 23.761 78 2.693 155 2.436 30 1.527

4 221 23 .289 84 2.379 162 2.321 22 2.103

5 251 24.812 72 2.483 134 2.435 28 1.562

6 246 22.98 74 2.568 179 2 .305 17 1.832

7 248 21.812 86 2.594 135 2.569 28 1.458

8 226 23.840 83 2.714 151 2.415 15 1.47

9 259 23 .578 79 2.461 139 2.365 21 1.438

10 240 23 .898 87 2.555 150 2.397 17 1.984

11 246 23.686 88 2.502 121 2.599 15 1.485

12 249 21.192 80 2.303 147 2.211 25 1.213

13 257 22.329 86 2.518 140 2.612 27 1.722

14 248 22 .92 86 3 .053 124 2.222 26 1.509

15 250 22.061 99 2.286 140 2.348 21 1.547

16 242 21.774 84 2.348 140 2.402 29 1.486

17 228 23.474 81 2.651 131 2.347 20 1.617

18 226 23.207 88 2.605 141 2.402 24 1.461

19 234 22.124 85 2.284 145 2.427 30 1.52

20 263 21.69 91 2 .201 154 2.564 22 1.927

Avg. 242.75 23.008 84.35 2.522 143.75 2.444 23 .2 1.621

71

In the CD-ROM stations subsystem, the simulated average

daily arrivals was between 221 and 263, the daily average

service time was between 21.2 and 24.8 minutes. The maximum

number in the waiting line was 7, and the longest average

waiting time was 7.5 minutes. In the librarian subsystem,

the simulated average daily numbers were: the reference

patrons helped by the librarians were between 121 to 179

with the service time between 2.21 to 2.89 minutes; the CD-

ROM users helped by the librarians were between 72 to 99

with the service time between 2.2 to 3.05 minutes; and the

librarians answered 15 to 30 telephone calls with the

service time of 1.21 to 2.1 minutes.

There were two minor differences between the pilot test

output data and the real system data (see table 1, table 2

and appendix C): (1) the output data had fewer users balking

and fewer users entering the waiting lines. Even the

maximum number in the queue and the average waiting time in

the queues were close; (2) at the system closing time, the

number of users in the system was larger than that in the

real system. The explanation of these differences is that

in the real system, the user interarrival time distribution

changes with the different time segments. For instance, in

the afternoon and evening, there are higher user arriving

rates; in the early morning and late night after 11:30 p.m.,

there are lower arriving rates. For simplicity, the model

used the same user arrival rate for the whole day simulation

72

which was an average of observations taken. These minor

differences did not bring any significant effect on the

resource utilization during the simulation process.

The results of pilot test not only can help us to test

the model but also can help us to determine how many times

the model needed to be run for a particular degree of

precision.

In the pilot run, we had: a = 0.05, R = 20, and the

degree of freedom f = 19.

Thus, the Vz width of confidence interval, I, was:

^= 0.025,19 '®' =2.093*6(0)

In the CD-ROM station submodel, 1=2.093*0.008=0.017.

Based on the pilot running data, Table 9 gives the lower and

upper limits of the 95% confidence interval of the average

utilization of the simulation model.

TABLE 9

Average Utilizations and 95% of the Confidence Intervals Based on 20 Replications

Avg Util s I L limit U limit

STATNS 0.646 0.036 0.017 0.629 0.663

LIBRNS 0.386 0.027 0.013 0.373 0.399

LIBRNl 0.352 0.027 0.013 0.339 0.365

LIBRN2 0.42 0.031 0.015 0.405 0.435

73

In the librarian submodel, for each librarian,

Iln1=2 .093*0.006 = 0.013 and ILN2=2 . 093*0 . 007 = 0 . 015 . If we

consider both LIBRNl and LIBRN2 together, the confidence

interval value was: ILN=2 . 093*0 . 006=0 . 013 .

Based on the pilot test and:

•V,

d(0)=-y/R

1 fca/2,f r-yfR

R can be solved from a given value of I,

Note that if the sample size is larger than 120, the t

value is 1.96. Therefore, for a large number of

replications, t=1.96 can be used for calculating the

estimation.

For the stations submodel, if the value of I is

selected as 0.01, a = 0.05, and s=0.036

R = 1.962 * (s/I)2 = 1.962 * (0.036/0.01)2 = 49.8

Thus the station submodel needs 50 replications to

obtain the level of accuracy. If the submodel is run 50

times, the t value should be 2.0 rather than 1.96. After

this correction, R = 51.84. So, at least, the station

74

submodel needed 52 replications.

Using the same method and the accuracy level, based on

the table 9, the librarian submodel had following results:

(1) For the whole storage LIBRNS, R = 28 (when

t=1.96). After the correction (use t=2.05), R = 2.052*7.29

= 30.618.

(2) With the same method, for the LIBRN1, R = 28.

After the correction, R = 30.618.

(3) For the LIBRN2, R = 36.9. After the correction,

R = 39.21.

These values mean that in order to get the selected

accuracy, the librarian submodel needed 40 replications

(selecting the larger one) of simulation.

Results from the Real System Data

For model validation purpose, if the simulated system

is an existing system, it is an important step to compare

the model output data with the data collected from the real

system.

Comparing the performance output by the simulation

model to the equivalent performance measures taken from the

real system is the most often suggested method of validating

a simulation model (Hoover and Perry, 1989, p.291). This

kind of comparison provides the researcher a general picture

of the difference between the simulation model and the real

system.

75

This kind of comparison has a common problem which

comes from the compared data sets themselves. The two data

sets are based on different time span. The data from the

simulation model probably depends on a much longer run time

than the time span used for collecting data from the real

system.

In this study, data collection from the real system was

done over four days. But the data from the model were based

on twenty days' time of the pilot run.

The collected data from the real system were used to

show a general picture of the real system and helped to

understand the differences between the real system and the

simulation model. Data from the real system are summarized

in tables 10 - 13.

(1) CD-ROM database connections:

According to the LAN system meter record, on average,

there were 656 connections per day from the workstations in

the Willis Library; there were about 9 minutes for each

connection, and every user retrieved 2 or 3 databases during

one visit (Table 10).

There were 67 available databases in this LAN system.

Based on the 2.46 average connections per user in table 10,

each user searched 4% (2.46/67=0.04) of the total database

titles during one visit.

76

TABLE 10

CD-ROM Database Connections

Date Conn. Avg T/Conn Users Conn/User

2-22 743 8.14 264 2 .81

2-23 691 8.04 268 2 .58

2-27 707 9.53 309 2.29

3-1 484 10.78 223 2 .17

Avg: 656.25 9.12 266 2.46

(2) Waiting lines:

According to the observations, usually the queues were

only formed during the peak times and less than 4 or 5

people were in the queue. Since there was almost no balking

in the waiting lines for the librarians' help or reference,

those 2 queues were considered as having no balking.

On average, about 17% of the arrived CD-ROM users had

to wait in the queue, and about 5% of the users simply left

without using the workstations (Table 11).

TABLE 11

Performance of the Waiting Line for CD-ROM Stations

Date CD-Users In Queue

% in Queue

Balk % of Balk

2-22 264 48 18.2% 18 6.8%

2-23 268 52 19.4% 17 6.3%

2-27 309 57 18.5% 21 6.8%

3-1 223 26 11.7% 0 0

Avg: 265.75 45.75 16.9% 14 5.3%

77

About 2 0% of the patrons for reference had to wait for

the librarians' help, and 18% of the CD-ROM users who needed

librarians' help could not get immediate service (Table 12).

TABLE 12

Performance of the Waiting Lines for Librarians

Date Ref Patrons

In Queue

% in Queue

CD Helps

In Queue

% in Queue

2-22 169 32 18.9% 88 18 20.5%

2-23 170 45 26.5% 92 16 17.4%

2-27 140 28 20% 110 19 17.3%

3-1 128 19 14.8% 79 13 16.5%

Avg: 151.75 31 20.4% 92.25 16.5 17.9%

In the real system, the user arrival rate was higher in

the early afternoon and evening. During these peak-time

segments, there was a greater possibility for waiting lines

to form due to the higher arrival rate. Since the

simulation model used the same interarrival distribution for

all running times, there were more patrons in the queues in

the real system than shown in the model generated data.

(3) Performance of the services:

Based on the real system, the data of average service

time was consistent. On average, a CD-ROM user took about

22 minutes to search the databases; the librarian could

solve the user encountered problem in 2.5 minutes. To

answer a reference question, it usually took a librarian

78

about 2.3 minutes; and it would take a librarian 1.5 minutes

to answer a telephone call (Table 13).

TABLE 13

Performance of the Services

Date CD-ROM stations service time

Help CD-ROM users service time

Reference service time

Answer calls service time

2-22 24.9 2.19 2.36 1.74

2-23 23.26 2.1 2 .76 1.64

2-27 18.28 2 .29 2.05 1.26

3-1 21.96 2.89 2 .02 1.35

Avg: 22.10 2.36 2 .30 1.5

System Data vs Model Generated Data

According to the pilot test, if the V2 width of the

variation interval estimate, I, was selected equal or

smaller than 0.01 and

a = 0.05, the station submodel should run at least 52

replications, and the librarian submodel should run at least

40 replications. To ensure the desired level of precision,

the station submodel was run 60 times, and the librarian

submodel was run 50 times. The average daily arrivals and

service times for the model generated data and the real

system data were compared in table 14. The categories in

the table can be considered to demonstrate the important

attributes with which to describe the system.

79

TABLE 14

The Means Comparison of the Real System Data and the Model Generated Data

CD-ROM users per day

Station service time

No. of help request from CD-ROM users

Service time to help CD users

Ref. per day

Ref. ser. time

Phone calls per day

Ser. time for calls

Real Sys

266 22.1 92.25 2.36 151.75 2.3 23 .5 1.5

Model 242.383 23.011 84.36 2.504 143.36 2.42 23 .94 1.661

Mann-Whitney Tests to the Difference

After reviewing the table 14, it can be noted that the

average numbers of the real system data and the model

generated data appeared much alike. Eight Mann-Whitney

tests were conducted to test that whether or not there was a

significant difference between the real system data and the

model generated data in the each category.

Mann-Whitney test is a nonparametric test that may be

used in place of t-test when assumptions can be justified.

It can be used to test equivalence between two medians from

different populations. Mann-Whitney test does not require

the assumption of normal distributions for the sample data,

and it does not require the same sample size (Kvanli,

Guynes, and Pavur, 1992, p.875).

The tests based on the data in table 1 (transactions

arrivals per day in the real system), table 13 (the service

times in the real system), and table 8 (model generated

arrivals and service times).

80

Eight Mann-Whitney tests were conducted with eight

groups of hypotheses:

(1) CD-ROM station users' daily arrivals.

Hl0: There is no significant difference between the

real system data and the simulation model generated data in

the CD-ROM station users' daily arrivals.

Hlj : There is a significant difference between the real

system data and the simulation model generated data in the

CD-ROM station users' daily arrivals.

(2) Number of help requests from CD-ROM station users.

H20: There is no significant difference between the


the number of help requests from CD-ROM station users.

There is a significant difference between the real


number of help requests from CD-ROM station users.

(3) Number of reference.



the number of reference.

£[3 There is a significant difference between the real


number of reference.

(4) Number of telephone calls.



81

the number of telephone calls.

H4-L: There is a significant difference between the real


number of telephone calls.

(5) CD-ROM station service time.



the CD-ROM station service time.

There is a significant difference between the real


CD-ROM station service time.

(6) Librarians' help time to CD-ROM users.



the librarians' help time to CD-ROM users.

1^: There is a significant difference between the real


librarians' help time to CD-ROM users.

(7) Librarians' reference service time.



the librarians' reference service time.

H71: There is a significant difference between the real


librarians' reference service time.

(8) The time to answer telephone calls.

82



the time to answer telephone calls.

HS^ There is a significant difference between the real


time to answer telephone calls.

The MINITAB statistical software provides a convenient

Mann-Whitney test procedure. Using this statistics software

package, for all these eight tests, all the null hypotheses

were failed to be rejected at a = 0.05 (see appendix D).

According to the test results, it was reasonable to

believe that statistically the numbers generated by the

simulation model had no difference to the numbers obtained

from the real system.

Utilizations Comparison Using the Queuing Theory

Suppose the interarrival time of the system

transactions {or users) is exponential distributed, all the

service times are exponential distributed, and the balking

problem is ignored, according to the queuing theory, the

service facility utilization is:

X P=

cp

c is the number of parallel service channels.

X=-

Avg-interarrival-time

83

^ Avg-service-time

According to the collected data from the stations

subsystem:

A = - ^ = 0.277 CD 960

The CD-ROM stations utilization:

0.277 0.277 p = = = 0 . 684 CD 9*0.045 0.405

Based on the 20 pilot runs, the model generated data

have an average utilization value of 0.646. The difference

is 0.038.

For the librarians' subsystem, the total number of

arrivals to the system is, on average, 267.5 per day (780

minutes), and for each transaction, the average service time

is 2.05 minutes; therefore,

X 0 . 3 4 3 LN 780

y = — — =0.488 LN 2.05

84

A 0.343 0.343 . _C1 o = = = =0.351 LN Cji 2*0.488 0.976

Compared with the model generated data of the LIBRNS,

the utilization is 0.386. The difference is 0.035.

Therefore, under the assumptions of the exponential

interarrival time and the service time distributions, it can

been seen that the real system and the simulation model

generate close values.

CHAPTER V

DIFFERENT CONFIGURATION EXPERIMENT

Computer simulation models have an important

application in the comparison of the different system

designs. Usually, the researcher runs the simulation model

with changes in the service facilities or the system policy

under the same system environment, then compares the

difference. This kind of comparison is based on the

assumptions of no changes in the interarrival time and the

service time distributions for the all replications in the

experiment. In this study, the station submodel was run for

11 different station arrangements, and the librarian

submodel was run for 2 different librarian arrangements.

For all the runs, the interarrival time, service time, and

the distributions were based on the collected data in the

Willis Library and kept the same values.

In measuring system performance, one measure or several

measures can be used. This study measured the utilizations

of the facilities, users' waiting rate, users' waiting time

if they have to wait in the queue, and other selected

measures.

85

86

Different Configurations

Under the present real system situation, the reference

desk doesn't have the space for more than 2 librarians, and

the number of the CD-ROM stations is usually about 10. So,

for realistic reasons, this experiment runs the model,

varying the number of the workstations represented by i,

from 5 to 15; and the number of librarians, referred to as

j, between 1 and 2. We have:

5 £ i £ 15, and Lj j = 1, 2.

Table 15 lists the station submodel running results

with 11 different configurations. It was found that there

was a sharp change in the waiting line performance between 5

stations and 6 stations. If there were only 5 stations,

64.2% of the CD-ROM users had to wait in queue (35.8% of

users with no wait) with the average waiting time of 13.6

minutes. If 6 stations were installed, the waiting rate

dropped to 38.8% (61.2% of users with no wait), and the

average waiting time in queue dropped to 6.8 minutes. This

would be about a 50% decrease in both measures.

For one or two assisting librarians at the reference

desk, the table 16 gives the relevant data. If one

librarian was on duty at the reference desk, the librarian

was busy 77% of the total time to help CD-ROM station users,

perform reference, and answer telephone calls. This left

the librarian with only 23% of the time to do other daily

routines. Under these circumstances, on average, 69% of the

87

help requests from CD-ROM station users were delayed (30.97%

of the help requests have no wait) with a waiting time of

5.9 minutes; 70% of the reference requests were delayed

(29.76% of the reference patrons have no wait) about 5.8

minutes.

TABLE 15

Simulation Results of Different Configurations of the Station Submodel

Avg Util

Std Err

Avg Sys Users

Avg Ser Time

Users with No Wait

% of Users with No Wait

Waiting Time in Q.

S5 0.910 0.005 193.0 22.924 69.15 35.8% 13.612

S6 0.842 0.004 211.017 23 .075 129.233 61.2% 6.845

S7 0.772 0.005 226.233 22.956 176.183 77.9% 4.618

S8 0.699 0.005 234.9 22.849 210.0 89.4% 3.202

S9 0.645 0.005 242.383 23.011 229.883 94.8% 2.664

S10 0.576 0.005 243 .067 22.754 238.467 98.1% 2.074

Sll 0.544 0.004 248.567 23.102 246.05 99% 1.36

S12 0.503 0.004 250.333 23.158 249.717 99.7% 0.619

S13 0.459 0.004 248.933 23.03 248.633 99.9% 0.184

S14 0.425 0.003 248.6 22.978 248.483 99.95% 0.114

S15 0.393 0.003 247.1 22.887 247.067 99.99% 0.036

Observation of the real system indicated that very

rarely was those a queue waiting for using a CD-ROM station.

This implies that increasing the number of workstations

would not bring about a significant increase in the number

of user arrival to the CD-ROM subsystem. Therefore it was

88

reasonable to assume that the number of CD-ROM station users

was a constant. With this assumption, if two librarians

were assigned to the reference desk, the CD-ROM users help

requests waiting rate would drop to 9% from 69%, the

reference requests waiting rate would drop to 11% from 70%,

and the average waiting time for both queues would be

decreased from 6 minutes to 1 minute. The librarian's busy-

time would be reduced to 38.3%. That means the librarians

would have 62.7% of the time to deal with other daily

routines.

TABLE 16

Simulation Results of Different Configurations of the Librarian Submodel

1 Librarian 2 Librarians

Avg Utilizations of the LIBRN 0.77 0.383

Std Error of the Utilization 0.007 0.004

Avg Number of CD-ROM Users Who Need Help 84.4 84.36

Number of Them Receiving Help without Wait 26.14 76.78

Avg Time in Min. for Users Who Wait 5.886 1.166

% of the No Wait 30.97% 91.01%

Avg Number of Patrons Who Need Reference 143.8 143.36

Number of Them Received Ref without Wait 42.8 128.12

Avg Time in Min. for Users Who Wait 5.782 1.132

% of the No Wait 29.76% 89.37%

Avg Service Time for CD-ROM Users 2.651 2.504

Avg Service Time for Reference 1 2.576 2.419

Avg Number of Telephone Calls Per Day 25.12 23 .94

Avg Time for Answering a Telephone Call 1.729 1.661

89

Confidence Interval Estimation

From tables 15 and 16, it can be observed that along

with an increase of CD-ROM stations and an increase of the

number of librarians, the waiting line situation showed a

definite improvement. That is, the user waiting rate and

the waiting time in the queue both decrease. But the trade

off for these improvements is that the system resource

utilizations show a decrease. Usually, we like to know an

estimate of how large the average utilization difference

might be between two configurations; a measure of the

accuracy of this estimation; and whether this difference is

statistically significant. A confidence interval estimation

can be used for these purposes.

For the confidence interval calculation, according to

Banks and Carson (1984, pp.451-465), we have:

s.e. (Yi-y2>=)J S l + g 2

R

s1 and s2 are the values of our selected samples'(mean

numbers) standard deviation (equal to the std. err. in the

tables). The degree of freedom is:

90

<<s2+s2)/.R)2 v = 2 -2

( (s2/J?) 2+ (s2/i?)2) / (n+1)

For example, when comparing the utilization difference

between a setting of 9 stations and a setting of 10

stations, we have the following results (the data of S9 and

S10 in the table 15 are used):

^-^=0.069

s.e. (Yx~Y2) = Sl+S2

R \ 5*10_5=9*10-60

v = (2 *0.0052/60)2 _2= 6 • 94*!Cr13 _2_ 6.94 _2 = 1 1 6_ 2 = 1 1 4

2 * (0 . 0052/60) 2/61 5 . 69 *10~15 0.0569

0 .025 .114 ~ 1-96

0.069 ± 1.96*9*10"4 = 0.069 ± 1.8*10"3

The results indicate that the CD-ROM station setting S9

and S10 has a difference in the stations' utilization of

0.069, and the 95% of confidence interval is: [0.0672,

0.0708]. This difference is statistically significant at

the 5% significant level, since 0 is not included in the

interval.

With the same calculation, the difference of the

91

utilization between assigning 1 librarian and assigning 2

librarians is 0.387, the 95% of confidence interval is

[0.3854, 0.3886], and the difference is also significant.

Regression Analysis

In the table 15 and 16, the data not only show us that

the values are changing along with a change in the system

configuration, but also it brings to light the relationship

of the variation between the variables. Regression analysis

can be used to determine the relationship between the system

performance and the system configurations.

Regression analysis is a method of studying the

relationship between two or more random variables. Since

the data are based on random samples, these statistical

relations are regression relations rather than a

mathematical functional relation. The linear regression

method uses a linear equation to estimate the relation

between data set {y} and data set {x}:

Y = AX + B + e, e: error

Where

Exy- (ExEy) /n

Ex2 - (Ex) 2 In

B=y-Ax

92

In this study, three regression relations were

investigated:

(1) The relationship between the utilization of the

workstations and the number of workstations.

From the values in table 15, a graph of utilization

versus the number of workstations can be plotted (figure 3).

This figure shows that the relation between the stations

utilization and the number of stations looks like a straight

line. It suggests that the linear regression can be used.

Utilization of CD-ROM stations

0.9

0.8

0.7

0.6

0.5

0.4

1.3 I S7 | S9 J S11 I S13 | S15

S 6 S8 S10 S12 S14

No. of Stations

Figure 3. Utilization and the Number of Stations

Using SAS program with the regression analysis

procedure, the regression equation is:

93

y = -0.052x + 1.132

Where y is the utilization of the workstations, x is

the number of the CD-ROM stations. The standard error of

the estimate is 0.026. The SAS program provides the graph

of the regression line and the upper and lower bound with

95% of confidence (figure 4). Some more detail relevant

statistics are also provided (see appendix F).

UTIL

0.9607

Plot of UTIL*STNS- Symbol used is Plot of U95*STNS. Symbol used is 'U'. Plot of L95*STNS. Symbol used is 'L'. Plot of UTHAT*STNS. Symbol used is 'P'.

0.9090 +

0.8573

0.8057 + L

0.7540

0.7023

0.6506

0.5989

0.5473 +

0.4956

0.4439 +

0.3922 +

0.3405 +

0 . 2 8 8 8

9 10 11 12 13 14 15

NUMBER OF STATIONS

Figure 4. Regression of Utilization on Number of Stations

94

This regression equation can be used to predict the

stations' utilization changing when the number of the

workstations needs to be changed (supposing the user

interarrival rate and the search time do not change).

(2) The relationship between the users' waiting rate

and the number of workstations.

A plot of waiting rate versus number of stations is

shown in figure 5. The data model is nonlinear.

Waiting Rate for* Stations

9 o m—m-1 I S13 T Sis S9 | S1 SIB S12

Mo. of Stations

Figure 5. CD-ROM Users Waiting Rate

In linear regression, error minimizing is based on the

least-squares estimation. While in the nonlinear

regression, the least-squares estimates of the parameters

95

can not be determined from a mathematical expression

(Ratkowsky, 1990, p.21). In order to deal with this

problem, one must obtain the minimum sum of squares by some

other means. One good method of doing this is finding a

method to convert the nonlinear model to a simple linear

model. In the figure 5, the data curve looks like a

negative exponential. It is reasonable to suppose that a

negative exponential equation:

y = a * eb/x , (a>0)

can be used to represent this curve. The above equation is

equivalent to:

In y =b/x + In a

Let X = 1/x, Y = In y, and C = In a.

The nonlinear regression problem is changed to a linear

regression problem:

Y = bX + C

The converted data are listed in the table 17. The

figure 6 gives the line graph after the conversion. This

line graph looks like a straight line which means the

conversion is successful and a linear regression can be used

to establish the relation.

96

TABLE 17

Converted Waiting Rate for Linear Regression

No. of Stations Waiting Rate(%)

1/x In y

5 64.2 0.200 4.162

6 38.8 0.167 3 . 658

7 22.1 0.143 3.096

8 10.6 0.125 2.361

9 5.2 0.111 1.649

10 1.9 0.100 0.642

11 1 0.091 0.000

12 0.3 0.083 -1.204

13 0.1 0.077 -2.303

14 0.05 0.071 -2.996

15 0.01 0.067 -4.605

Waiting Rate After Conversion

5

4

3

2

1

£ 0 rH a

II > -1

izr

-2

-3

-4 - /

5 •

0.067 | 0.077 | 0.091 I 0.111 1 0.143 1 0*2 0.071 0.083 0.1 0.125 0.167

X=1/x

Figure 6. Converted Waiting Rate

97

Using SAS program, The linear regression equation is

given as:

Y = 61.85X - 6.54

where Y = In y, X = 1/x. Here the standard error of the

estimate is 1.26.

CVTWR | 5 +

4 +

0 +

—2 +

-3

-4 +

-5 +

REGRESSION OF CONVERTED WAITING RATE ON NUMBER OF STATIONS

Plot of CVTWR*CVTST. Symbol used is Plot of U95*CVTST. Symbol used is 'U'. Plot of L95*CVTST. Symbol used is 'L'. Plot of WRHAT*CVTST. Symbol used is 'P'.

2 +

1 + u

0.06 0.08 0.10 0.12 0.14

CVTST

NOTE: 1 obs hidden. 6 obs were out of range.

0.16 0.18 0.20

Figure 7. Converted Linear Regression on the Waiting Rate

98

Figure 7 plots the regression line with 'P' and the

upper and lower limits with 95% of confidence. The original

data are plotted by '*'.

To convert it back to the nonlinear regression

equation, the linear equation becomes:

y = 0.0014 * e 61.85/x

Where y% is waiting rate, x is the number of

workstations. This formula can be used to estimate the

users' waiting rate and the number of CD-ROM workstations on

the LAN.

TABLE 18

Converted Waiting Time for Linear Regression

No. of Stations Waiting Time 1/x In y

5 13.612 0.200 2.611

6 6.845 0.167 1.924

7 4.618 0.143 1.530

8 3 .202 0.125 1.164

9 2.664 0.111 0.980

10 2.074 0.100 0.729

11 1.36 0.091 0.307

12 0.619 0.083 -0.480

13 0.184 0.077 -1.693

14 0.114 0.071 -2.172

15 0.036 0 . 067 -3.324

99

(3) The relationship between the users average waiting

time in the queue and the number of the workstations.

Malting Time in the Queue

S9 | Si! | S10 S12 S14

Mo. of Stations

Figure 8. Users' Waiting Time in the Queue

Waiting Tine After Conversion

3

2

1

0 >,

c J3

> -1 / -2 --3 - / 4

0.067 | 0.077 | 0.091 | 0.111 | 0.143 1 0.200 0.071 0.003 0.100 0.125 0.167

K=1/x

Figure 9. The Linear Regression after Conversion

100

Like (2), this relation is also nonlinear (figure 8).

Using the same method in the preceding analysis, it can be

converted to a linear regression problem. The relevant

figure and table are figure 8, 9, and table 18.

The linear regression equation is:

Y = 36.44 X - 3.86

Where Y = In y and X = 1/x. The standard error of the

estimate is 1.046.

CVTWT | 5 +

2 +

1 +

- 2 +

REGRESSION OF CONVERTED WAITING TIME IN THE QUEUE

Plot of CVTWT*CVTST. Symbol used is Plot of U95*CVTST. Symbol used is 'U'. Plot of L95*CVTST. Symbol used is 'L'. Plot of WRHAT*CVTST. Symbol used is 'P'.

0.06 0.08 0.10 0.12 0.14

CVTST NOTE: 1 obs were out of range.

0.16 0.18 0.20

Figure 10. Converted Linear Regression on the Waiting Time

101

The regression line with the 95% confidence interval is

plotted by SAS (figure 10).

After converting back, the linear regression equation

becomes:

Y = 0.021 * e36-44/x

With this regression equation, the CD-ROM users'

average waiting time (y minutes) in the queue can be

predicted by the number of the workstations (x).

Utilization of the Librarians

Since only two choices for the number of librarians

were investigated, regression analysis is not applicable.

We can simply use bar chart to show the difference between

these two assignments (Figure 11).

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0 . 2

0.1

Comparison of Assigning Different No. of Librarians

umjm Mo. of Librarians

^Utilization (\\]Help Waiting Rate ^ R e f . Waiting Rate

Figure 11. Comparison of the Two Different Librarian Assignments

102

In this bar chart, it can be find that the CD-ROM

users' help demands waiting rate and the reference patrons'

waiting rate are sharply decreased when two librarians are

assigned. If there is only one librarian at the reference

desk, this librarian almost does not have any spare time

other than helping CD-ROM users, providing references and

answering telephone calls. Since a reference librarian must

have some time to deal with the daily routine jobs, one

librarian cannot handle this reference desk. Two librarians

are necessary to keep this system running smoothly.

CHAPTER VI

SUMMARY AND CONCLUSION

Summary

This research created a computer simulation model for a

library CD-ROM LAN system. The model represented the

configuration of CD-ROM LAN in a library, then was used to

study system optimization.

The relevant literature was reviewed in six areas: (1)

the development of CD-ROM systems in libraries, (2) the

development of CD-ROM LAN, (3) decision making on CD-ROM

LAN, (4) operations research in libraries, (5) simulation

studies in libraries, and (6) special purpose simulation

languages. With LAN technology, isolated CD-ROM

workstations were networked for sharing of CD-ROM databases,

increasing data integrity, increasing system reliability and

security, and allowing remote access.

In a library CD-ROM LAN system design, there are many

decision making problems. The system resources utilization

problem and the users' waiting line problem are two major

problems related to the system decision making in the system

design. Computer simulation is a powerful way to study such

problems.

103

104

A simulation model generates an artificial system to

imitate a real system. The simulation model is based on the

collected data of the real system. The data in this study

were collected on four randomly selected days in the middle

of a semester. In order to get valid and accurate data, two

methods were used: direct observation and the use of the LAN

system metering software. Before the formal data

collection, a pre-observation was done; the users'

activities and the system resources' activities were

analyzed. Based on the analysis, the data collection forms

were designed. During observation, the activities taking

place during the entire days were recorded and the

observation did not interfere with the users' normal

behavior.

Based on the observations, the data analysis, and

discussions with the librarians, the concept model and the

logic model were generated. Using GPSS/H, the computer

simulation model was developed. Corresponding to the system

resources, workstations and reference librarians, the

simulation model was divided into two submodels: station

submodel and librarian submodel. The station submodel dealt

with the CD-ROM stations' users, based on a running time of

16 hours per day (8:00 a.m. - 12:00 midnight). The

librarian submodel dealt with the help requests from the CD-

ROM users, the patrons for reference, and telephone calls,

based on a running time of 13 hours per day (9:00 a.m. -

105

10:00 p.m.).

The following procedures were followed for optimizing

validation of the model: (1) Discussions with the

librarians. (2) Careful collection of data. (3) Use of an

animation technique to show the CD-ROM users' coming and

leaving process. (4) Use of a pilot run. (5) Use of

queuing theory to calculate average utilization of resources

based on the collected data; comparing with the average

utilization based on the model generated data and checking

whether the difference was small.

The pilot run indicated how many replications were

needed to satisfy a certain accurate confidence interval

under certain probability. For this study, if the estimate

variation of the 95% confidence interval was selected as

0.01, the station submodel needed 52 replications; and the

librarian submodel needed 40 replications.

In order to get the relationship between the system

performance and different system configurations, the

simulation model was run with a wide variety of system

resources. Based on the pilot study, the station submodel

was run 60 replications for each resources changed; the

librarian submodel was run 50 times for each resources

changed.

In the simulation, the number of workstations varied

from 5 to 15, and the number of librarians from 1 to 2.

Using the station submodel generated data, regression

106

analysis was used to find the relationship of the station

utilization to the number of stations, the relationship of

the users' waiting rate to the number of stations, and the

relationship of the users' waiting time in the queue to the

number of stations. The last two were non-linear

relationships but they were transformed to linear regression

problems.

Findings

According to the collected data in the Willis Library,

University of North Texas, a middle size academic library

with 9 workstations on the CD-ROM LAN and 51 CD-ROM database

titles, the followings were found:

1. The empirical distributions of the observed data

can be used to build a valid simulation model.

2. For using queuing theory to do prediction, the all

interarrival time distributions can be assumed as negative

exponential type. The all service time distributions can be

assumed as negative exponential type, too.

3. On average, each day, there were 266 CD-ROM station

users with 656 connections to the databases; on average,

each connection lasted 9.12 minutes, and each user had 2.46

database connections. The average interarrival time of the

CD-ROM users was 3.41 minutes; the average searching time

was 22.1 minutes.

4. On average, each day, there were 152 library

107

patrons asking for reference; librarians could process each

reference in 2.3 minutes.

5. On average, each day, there were 92 CD-ROM users'

help requests, and librarians could deal with each help

request in 2.36 minutes.

6. On average, each day, the librarians answered 23

telephone calls which lasted for 1.5 minutes for each call.

7. On average, 16.9% of the CD-ROM station users had

to wait in the queue; 20.4% of the patrons needing reference

help could not get immediate service; and 17.9% of the CD-

ROM users' help requests had been delayed.

8. In eight categories, the data from the real system

and the data from the simulation model did not have

significant difference based on the Mann-Whitney test. The

eight categories are: (1) the arrivals of the CD-ROM station

users, (2) the help requests from the CD-ROM station users,

(3) the arrivals of the patrons for reference, (4) the

arrivals of telephone calls, (5) the CD-ROM station's

service time, (6) the librarians' help time to the CD-ROM

users,(7) the reference service time, and (8) the time to

answer telephone calls.

9. Based on queuing theory, stations utilization was

calculated to be 0.684, the model generated average

utilization was 0.646. The calculated librarians'

utilization was 0.351, the model generated value was 0.386.

Both of the differences were small.

108

10. According to the simulation result, if assigned 1

librarian when the system has 9 stations, the librarian

would be busy on the 77% of the total time. In this

situation, 69% of the help requests from CD-ROM users and

70% of the reference requests would have to wait in a queue.

11. If the number of workstations increased from 5 to

6, the users' waiting rate would drop to 3 8.8% from 64.2%;

the waiting time in queue would drop from 13.6 to 6.8

minutes. Therefore, changing workstations from 5 to 6 would

bring a sharp change to the users' waiting rate.

Conclusion

Based on the findings above, the following conclusions

have been derived:

1. The computer simulation model created for the CD-

ROM LAN system in this study is valid and accurate. The

data generated by this simulation model can be used for

other relevant studies. This model can be used for other

middle sized academic libraries, if the environment is close

to that of the Willis Library at the University of North

Texas. If more accurate results are needed, the designer

can change the input variables which would include

interarrival time values, service time values, and the

number of resources according to their own situation.

2. The simulation model output data of the

utilizations have a nature of consistency. The variation at

109

the 95% confidence interval is less or equal 0.02 (1=0.01).

3. Between the utilization of the CD-ROM workstations

and the number of workstations, there is following

relationship:

U = -0.052S + 1.132

Where U is the utilization and S is the number of CD-

ROM stations, the standard error of the estimate is 0.026.

4. Between the CD-ROM users' waiting rate and the

number of workstations, there is this relationship:

Wr = 0.0014 * e61"85/s

Where Wr% is the waiting rate and S is the number of

the CD-ROM stations.

5. If a CD-ROM user entered a queue, the waiting time

and the number of the workstations has this relationship:

Wt = 0.021 * e36'44/s

Where Wt is the predicting waiting time (in minute) if

a user entered the queue; S is the number of the CD-ROM

stations.

6. Along with an increase in the number of CD-ROM

stations, the utilization of the workstations decreased.

110

7. As a minimum, this system needs 6 CD-ROM

workstations and 2 librarians.

The overall objective of this study was to demonstrate

the feasibility of using simulation in designing

technological configurations in libraries. This study

confirmed the feasibility of the method.

Recommendations for Further Study

This simulation model was generated based on the

collected data during whole day time periods. During one

day, library patrons arrival rate is changeable. If

possible, for higher degree of accuracy, the data could be

analyzed by dividing whole day into several time segments

and obtaining the different arrival rates for each time

segments. However, this tradeoff would result in data

analysis becoming more complex.

Also, future studies might investigate the use of

simulation in other library areas where technology is used.

For example, workstations in technical services, user online

catalog access points, and business and personnel systems in

large libraries.

APPENDIX A

111

112

DATA COLLECTION SHEET

Observation Date: User No.

The user is: Male Female

Time of arriving: Time of leaving without searching:_

Time of beginning to search: Station number:

Time of need librarian's help: ; ;

Librarian's help begins at:

Librarian's help ends at:

Time of the search finishing:

Time of leaving

Any unusual events:

113

THE DAILY ROUTINE ACTIVITIES OF THE LIBRARIAN

Activities Occurren -ce time

The user is in Q.?

Time of service start

Time of service end

Service time

Other

APPENDIX B

114

115

CD-ROM Users Interarrival

SAS 10:46 Monday, November 27, 1995 1

Analysis Variable : X

N Obs N Minimum Maximum Mean Std Dev

1060 1060 0.0300000 27.9700000 3.4149528 3.2332411

SAS 10:46 Monday, November 27, 1995

Cumu1at ive Cumu1at ive X Frequency Percent Frequency Percent

2 432 40.8 432 40.8 4 308 29.1 740 69.8 6 158 14.9 898 84 .7 8 79 7.5 977 92.2 10 42 4.0 1019 96.1 12 16 1.5 1035 97.6 14 11 1.0 1046 98 .7 16 2 0.2 1048 98 .9 18 4 0.4 1052 99.2 20 4 0.4 1056 99.6 24 2 0.2 1058 99.8 28 2 0.2 1060 100.0

116

CD-ROM Users Interarrival Time Distribution

10:46 Monday, November 27, 1995

FREQUENCY OF X

FREQUENCY

400 +

350 +

300 +

250 +

200 +

150 +

100 +

50 +

•k it "k

•kit k

* ie it

it it it

• it it

it it it

it it it

it it it

•kit*

it it it

it-kit

it-kit

it it it k it it

-k kit it it k

kit it it it it

•kit it it kit

ititk it it it

it it k kit-k

it iik kit-k

it it it kit it

•kkk -k it it

•kitit it it k

kitit it "k it

•kit it it k it

•kit-k it kit

it it k k-kit

it it it kit-k

•k k it it it -k * * *

-k it it it-kk kit-k

kit-k -k-kit •kitit

ititk it kit it it "k

ititk kit-k -k-kk

"k k it it-kit it k it

it it it •k-kk k-k-k

itit-k it k it

•kit k it it it * * * -k-k-k

it it it kit-k -k-kk -k-k-k

it kit it-kit it -k it -k-kit

kit-k it-kk -k-k-k -kit-k

it it it it k it -k-k-k k-k-k it k it

it-kk ik-kit k-k-k it-kk kit-k

it it k kit-k -k-k-k -k-k-k -kit-k

it-kk k-k-k -k-k-k it it it itit-k

2 4 6 8 10

* it k * * *

* * *

12 14

X

16 18 20 24 28

117

CD-ROM Stations Service Time




1008 1008 0.5900000 143.6000000 21.9596329 16.4147078


Cumulative Cumulative X Frequency Percent Frequency Percent

10 252 25.0 252 25.0 20 300 29.8 552 54 .8 30 208 20.6 760 75.4 40 117 11.6 877 87.0 50 67 6.6 944 93 .7 60 31 3.1 975 96 .7 70 17 1.7 992 98 .4 80 9 0.9 1001 99.3 90 5 0.5 1006 99.8 100 1 0.1 1007 99.9 150 1 0.1 1008 100.0

118

CD-ROM Stations Service Time Distribution


FREQUENCY OF X

FREQUENCY

300 + kkkk

kkkk

kkkk

kkkk

270 f kkkk

kkkk

k kk ie kkkk

k k k k kkkk

240 f k k k k kkkk

k k k k kkkk

kkkk kkkk

kkkk kkkk

210 + kkkk kkkk kkkk

kkkk kkkk kkkk

kkkk kkkk kkkk

kkkk kkkk kkkk

180 t- kkkk kkkk kkkk

kkkk kkkk kkkk

kkkk kkkk kkkk

kkkk kkkk kkkk

150 + kkkk kkkk kkkk

kkkk kkkk kkkk

kkkk kkkk kkkk

kkkk kkkk kkkk

120 + kkkk kkkk kkkk kkkk

kkkk kkkk kkkk

kkkk kkkk * * * * kkkk

kkkk kkkk * * * * kkkk

90 + kkkk kkkk * * * * kkkk

kkkk kkkk kkkk kkkk

kkkk kkkk kkkk kkkk

kkkk kkkk kkkk kkkk * * *• *

60 + kkkk kkkk kkkk kkkk k k k k

kkkk kkkk kkkk kkkk kkkk

kkkk • * * * " * kkkk kkkk kkkk

kkkk * * * * kkkk kkkk kkkk

30 + kkkk kkkk kkkk kkkk kkkk




10 20 30 40 50

k kk •}if *• * *

* * -k k

kkkk

k kk k

kkkk

60

X

70 80 90 100 150

119

CD-ROM Users' Help Requests




365 365 0.2000000 47.8500000 8.2369041 7.3464779



5 150 41.1 150 41.1 10 113 31.0 263 72 .1 15 52 14.2 315 86.3 20 23 6.3 338 92 .6 25 12 3.3 350 95.9 30 9 2.5 359 98 .4 35 1 0.3 360 98 .6 40 3 0.8 363 99.5 50 2 0.5 365 100.0

120

CD-ROM Users Help Requests Interarrival Time Distribution


FREQUENCY OF X

FREQUENCY

140 +

120 +

100

80 I +

60 +

40

20 +

* * * * *

* * * * *

* * * * *

* * * * *

* * * * *

* * * * *

* * * * *

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* * * * * * * * * * * * * * * * * * * *

* * * * * * * * * * * * * * * * * * * *

5 10 15 20

* * * * * * * * * *

* * * * * * * * * *

25

X

30 35 40 50

121

Librarian's Service Time for CD-ROM Users' Help Requests




369 369 0.5200000 11.8500000 2.3467209 1.5985101



1 32 8.7 32 8.7 2 152 41.2 184 49.9 3 90 24.4 274 74 .3 4 51 13.8 325 88.1 5 21 5.7 346 93.8 6 10 2.7 356 96.5 7 4 1.1 360 97.6 8 2 0.5 362 98.1 9 3 0.8 365 98.9 10 2 0.5 367 99.5 11 1 0.3 368 99.7 12 1 0.3 369 100.0

122

FREQUENCY

CD-ROMs Help Service Time Distribution


FREQUENCY OF X

* • * *

* * *

140 b •kic ie

* * *

* * *

ie ie if

120 h * * *

ie * *

ic ie ie

ie ie ie

100 i- kkie

* * *

* * * kkk

kk k kkk

80 H kk k kkk

k k k kkk

k k k kkk

kkk kkk

60 + k k k kkk

kkk kkk

kkk kkk kkk

kkk kkk kkk

40 + kkk kkk kkk

kkk kkk kkk

ie ic ie kiek kkk kkk

kkk kkk kkk kkk

20 + kkie kkk kkk kie k * * *

kkk kkk kkk ie k k kkie

* * * kkk kkk kkk kkk

* * * kkk kkk kkk kkk

1 2 3 4 5

* * * * * *

10 11 12

X

123

Reference Patrons Interarrival Time




603 603 0.0200000 29.6800000 5.0864511 4.3310855



2 160 26 .5 160 26.5 4 145 24 .0 305 50.6 6 109 18 .1 414 68.7 8 61 10 .1 475 78.8 10 51 8 .5 526 87.2 12 31 5 .1 557 92.4 14 20 3 .3 577 95.7 16 9 1 .5 586 97.2 18 6 1 .0 592 98 .2 20 5 0 .8 597 99.0 22 2 0 .3 599 99.3 24 3 0 • 5 602 99.8 30 1 0 .2 603 100.0

124

References Interarrival Time Distribution


FREQUENCY OF X

FREQUENCY

160 + * * *

* * *

* * *

* * • kkk

140 f • * kkk

•* * *• kkk

* k k kkk

kkk kkk

120 f k k k kkk

it-kit kkk

k k it kkk kkk

k k k kkk kkk

100 t- k k k kkk kkk

k k k kkk kkk

k k k kkk kkk

kkk kkk kkk

80 i- kkk kkk kkk

* * •* kkk kkk

kkk kkk kkk

* * * kkk kkk

60 h kkk kkk kkk kkk

kkk kkk kkk kkk

kkk kkk kkk kkk * * *

kkk kkk kkk kkk kkk

40 + kkk kkk kkk kkk kkk

kkk kkk kkk kkk kkk

kkk kkk kkk kkk kkk * * *

kkk kkk kkk kkk kkk k k k

20 + kkk kkk kkk kkk kkk kkk kkk

kkk kkk kkk kkk kkk kkk kkk



2 4 6 8 10 12 14

* * * it k k

30

X

125

Reference Librarians Service Time for General References




606 606 0.2800000 21.0900000 2.3259901 2.0243890



1 92 15 .2 92 15.2 2 255 42 .1 347 57.3 3 132 21 .8 479 79.0 4 53 8 .7 532 87.8 5 26 4 .3 558 92.1 6 18 3 .0 576 95.0 7 12 2 .0 588 97.0 8 3 0 .5 591 97.5 9 5 0 .8 596 98 .3 10 3 0 .5 599 98.8 12 4 0 .7 603 99.5 15 1 0 .2 604 99.7 16 1 0 .2 605 99.8 21 1 0 .2 606 100.0

FREQUENCY

126

Reference Librarians Service Time Distribution


FREQUENCY OF X

240 +

210 +

180 +

150 +

120 +

90

60 +

30 +

* * *

* * *

* * *

ie ie ie

ie ie ie

ie ie • * * *

* ie it

ie ie ie

ie ie ie

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1 8

X

10 12 15 16

127

Telephone Calls Interarrival Time




90 90 0.5000000 173.7300000 29.8284444 31.3766751



10 24 26 .7 24 26 .7 20 15 16 .7 39 43 .3 30 20 22 .2 59 65.6 40 8 8.9 67 74 .4 50 8 8.9 75 83.3 60 6 6.7 81 90.0 70 4 4.4 85 94 .4 100 1 1.1 86 95.6 110 1 1.1 87 96.7 130 1 1.1 88 97.8 170 1 1.1 89 98.9 180 1 1.1 90 100.0

FREQUENCY

128

Telephone Calls Interarrival Time Distribution


FREQUENCY OF X

24 + I

23 +

I 22 +

21 + I I 20 + I l 19 +

18 + l !

17 + I I

16 + I I

15 + i I

14 + l I 13 + l I 12 +

11 + I I

10 +

I 9 + I

8 +

I 7 + I

6 + I

5 + I I 4 + l I 3 +

2 + I I 1 +

* * * *

* * * *

* * * *

* * * *

* * * *

* * * *

* * * *

* * * *

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****

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* A * * * * * *

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****

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* * * *

* * * *

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* * * *

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* * * *

* * * *

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* * * *

****

* * * *

* * * *

* * * *

* * * *

* * * *

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10 20 30 4 0 5 0 60 70 100 110 1 3 0 1 7 0 180

129

Service Time of Answering Telephone Calls



N Obs N

94 94

Minimum

0.2500000

Maximum

8.0100000

Mean

1.4660638

Std Dev

1.2256315



1 40 42 , .6 40 42 .6 2 36 38 , .3 76 80.9 3 12 12 , .8 88 93 .6 4 2 2 , .1 90 95.7 5 1 1, .1 91 96 .8 6 1 1, .1 92 97.9 7 1 1, .1 93 98.9 9 1 1. .1 94 100.0

FREQUENCY

40 +

35 +

30 +

25 +

20 +

15 +

10 +

130

Telephone Call Service Time Distribution


FREQUENCY OF X

+ * * * * *

* * * * *

* * * * *

* * * * *

* * * * * * * * * *

+ * * * * * * * * * *

* * * * * * * * * *

* * * * * * * * * *

* * * * * * * * * *

* * * * * * * * * *

+ * * * * * * * * * *

* * * * * * * * * *

* * * * * * * * * *

* * * * * * * * * *

* * * * * * * * * *

+ * * * * * * * * * *

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* * * * * * * * * *

* * * * * * * * * *

* * * * * * * * * *

+ * * * * * * * * * *

* * * * * * * * * *

* * * * * * * * * *

* * * * * * * * * *

* * * * * * * * * *

+ * * * * * * * * * *

* * * * * * * * * *

* * * * * * * * * *

* * * * * * * * * * * * * * *

* * * * * * * * * * * * * * *

+ * * * * * * * * * * * * * * *

* * * * * * * * * * * * * * *

* * * * * * * * * * * * * * *

* * * * * * * * * * * * * * *

* * * * * * * * * * * * * * *

+ * * * * * * * * * * * * * * *

* * * * * * * * * * * * * * *

* * * * * * * * * * * * * * *

* * * * * * * * * * * * * * *

* * * * * * * * * * * * * * *

1 2 3

* * * * * * * * * *

* * * * * * * * * * * * * * *

X

APPENDIX

131

132

STUDENT GPSS/H RELEASE 2.01 (EP292) 23 Aug 1995 16:40:55

LINE# STMT# IF DO BLOCK# *LOC OPERATION A,B,C,D,E,F,G

FILE: PROJCD.gps

COMMENTS

1 1 *

2 3

2 3

* THIS PROGRAM SIMULATES THE LIBRARY CD-ROM LAN SYSTEM USING PERFORMANCE

4 4 SIMULATE 5 5 *

6 6 * AMPERVARIABLE DECLARATION

8 8 INTEGER &I 9 9 REAL &AUTI,&ASYS,&ASERt &ATQL t &AENT,&NOWT,&MAXQ

10 10 LET &MAXQ=-999999. 11 11 *

12 12 STORAGE DECLARATION 13 13 +

14 14 STORAGE S(STATIONS),9 15 15 +

16 16 + DEFINE FUNCTIONS 17 17 +

18 18 ARRIV FUNCTION RN(l)fC12 19 19 0.408,2/0.6 9 8,4/0.847,6/0.922,8/0.961,10/0.9 76,12/0.9 87,14 20 20 0.989,16/0.9 92,18/0.996,20/0.998,24/1.0,28 21 21 SERV FUNCTION RN(1),C11 22 22 0.25,10/0.548,2 0/0.754,3 0/0.8 7,40/0.937,50/0.9 67,6 0/0.9 84,70 23 23 0.993,80/0.99 8,9 0/0.999,100/1.0,150 24 24 *

25 25 * GPSS/H BLOCKS 26 26 *

27 27 1 GENERATE FN(ARRIV) USER ARRIVES WITH DEFINED DISTRIBUTION 28 28 2 TEST G Q(SYS),9,LN IF STORAGE IS FULL, 3 6% OF THE 29 29 3 TRANSFER .36,,EXIT USERS LEFT, 64% WILL WAIT IN LINE 30 30 4 LN QUEUE SYS USER ENTERS THE SYSTEM 31 31 5 QUEUE LINE 32 32 6 ENTER STATIONS 33 33 7 DEPART LINE 34 34 8 QUEUE SERV RECORD THE SERVICE TIME 35 35 9 ADVANCE FN(SERV) USING DEFINED DISTRIBUTION 36 36 10 LEAVE STATIONS 37 37 11 DEPART SERV 38 38 12 DEPART SYS 39 39 40 40 13 EXIT TERMINATE 41 41 42 42 43 43 * TIME SEGMENT 44 44 *

45 45 14 GENERATE 960 SIMULATE 1 DAY (16 HOURS=960 MIN) 46 46 15 TERMINATE 1 47 47 *

48 48 # CONTROL STATEMENT 49 49 *

50 50 1 DO &I=1,20 REPEAT 2 0 TIMES 51 51 1 CLEAR CLEAR ALL STATISTICS 52 52 1 START 1 START SIMULATION WITH PRINT 53 53 1 LET &ASYS=&ASYS+QT(SYS) 54 54 1 LET &AUTI=&AUTI+SR(STATIONS) 55 55 1 LET &ASER=&ASER+QT(SERV) 56 56 1 LET &ATQL=&ATQL+QX(LINE) 57 57 1 LET &AENT=&AENT+QC(LINE) 58 58 1 LET &NOWT=&NOWT+QZ(LINE) 59 59 1 1 IF &MAXQ<QM(LINE) 60 60 1 1 LET &MAXQ=QM(LINE) 61 61 1 END IF 62 62 ENDDO 63 63 LET &ASYS=&ASYS/20. 64 64 LET &AUTI=&AUTI/2 0. 65 65 LET &ASER=&ASER/20. 66 66 LET &ATQL=&ATQL/20. 67 67 LET &AENT=&AENT/2 0. 68 68 LET &NOWT=&NOWT/2 0. 69 69 PUTPIC FILE=ANSCDR,LINES=11,(&AUTI,&ASYS,&ASER,&AENT,&NOWT,&MAXQ,&ATQL) 70 70

PUTPIC FILE=ANSCDR,LINES=11,(&AUTI,&ASYS,&ASER,&AENT,&NOWT,&MAXQ,&ATQL)

71 71 SIMULATION RESULT 72 72 73 73 74 74 AVERAGE UTILIZATION: *+*.++* 75 75 USER AVERAGE TIME IN THE SYSTEM: 76 76 STATION AVERAGE SERVICE TIME: 77 77 AVERAGE NUMBER OF SYSTEM USERS PER DAY: **+.+++ 78 78 AVERAGE NUMBER OF THE USERS WITH NO WAIT: ***.*++ 79 79 MAXIMUM NUMBER IN THE WAITING LINE: ***_*** 80 80 AVERAGE WAITING TIME IN THE WAITING LINE: ***.*** 81 81 82 82 END

133

ENTITY DICTIONARY (IN ASCENDING ORDER BY ENTITY NUMBER;

Queues: 1=SYS 2=SERV 3=LIS

Storages: l=STATIONS

=> VALUE CONFLICT.)

Func t i ons: 1=ARRIV

Random Numbers: 1

Integer &Vars: 1=1

Real &Vars: 1=AENT 7=N0WT

Files: 1=ANS CDR

MBOL VALUE EQU DEFNS

2=SERV

4=ATQL

REFERENCES BY STATEMENT NUMBER

STATIONS 1 Absolute 14

EXIT 13 40 Block 29 LN 4 30 Block 28

LINE 3 Queue 31 33 56 57 58 SERV 2 Queue 34 37 55 SYS 1 Queue 28 30 38 53

STATIONS 1 14 Storage 32 36 54

ARRIV 1 18 Function 27 SERV 21 Function 35

1 1 Random Nmbr 18 21

I 1 8 Integer 50

AENT 1 9 Real 57 57 67 67 69 ASER 2 9 Real 55 55 65 65 69 ASYS 3 9 Real 53 53 63 63 69 ATQL 4 9 Real 56 56 66 66 69 AUTI 5 9 Real 54 54 64 64 69 MAXQ 6 9 Real 10 59 60 69 NOWT 7 9 Real 58 58 68 68 69

ANSCDR 1 File 69

STORAGE REQUIREMENTS (BYTES)

COMPILED CODE: COMPILED DATA: MISCELLANEOUS: ENTITIES: COMMON:

1490 652 467 576

10000

TOTAL: 13185 GPSS/H MODEL SIZE:

CONTROL STATEMENTS 26 BLOCKS 15

Simulation begins.

RELATIVE CLOCK: 960 . 0000 ABSOLUTE CLOCK: 960.0000

BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 269 11 252 2 269 12 252 3 13 EXIT 259 LN 262 14 1 5 1 262 15 1 6 261 7 261 8 261 9 9 261 10 252

--AVG-UTIL-DURING--STORAGE TOTAL AVAIL UNAVL

TIME TIME TIME STATIONS 0.728

QUEUE

SYS SERV LINE

MAXIMUM CONTENTS

12 9 3

ENTRIES AVERAGE CURRENT PERCENT CAPACITY TIME/UNIT STATUS AVAIL

261 24.096 AVAIL 100.0 9

AVERAGE CONTENTS

6.630 6 .551 0 . 079

TOTAL ENTRIES

262 261 262

ZERO ENTRIES

0

PERCENT ZEROS

AVERAGE TIME/UNIT

24.294 24.096 0.290

AVERAGE CONTENTS

6.551

$AVERAGE TIME/UNIT

24.294 24.096 2.053

CURRENT MAXIMUM CONTENTS CONTENTS

9 9

QTABLE NUMBER

CURRENT CONTENTS

10 9

RANDOM STREAM

1

ANTITHETIC VARIATES

OFF

INITIAL CURRENT SAMPLE CHI-SQUARE POSITION POSITION COUNT UNIFORMITY

100000 100544 544 0.91

STATUS OF COMMON STORAGE

8128 BYTES AVAILABLE 1872 IN USE 2160 USED (MAX)

RELATIVE CLOCK: 960.0000 ABSOLUTE CLOCK: 960.0000

134

BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 249 11 239 2 249 12 239 3 14 EXIT 244 LN 244 14 1 5 244 15 1 6 244 7 244 8 244 9 5 244 10 239

--AVG-UTIL-DURING--STORAGE TOTAL AVAIL UNAVL CURRENT PERCENT

TIME TIME TIME TIME/UNIT STATUS AVAIL STATIONS 0 . 708 244 25, ,072 AVAIL 100.0

QUEUE MAXIMUM AVERAGE TOTAL ZERO PERCENT CONTENTS CONTENTS ENTRIES ENTRIES ZEROS

SYS 13 6 .492 244 0 SERV 9 6 .372 244 0 LINE 4 0 . 120 244 213 87.3

RANDOM ANTITHETIC INITIAL CURRENT SAMPLE CHI-SQUARE STREAM VARIATES POSITION POSITION COUNT UNIFORMITY

1 OFF 100544 101052 508 0.55



RELATIVE CLOCK: 960.0000 ABSOLUTE CLOCK: 960. , 0000


AVERAGE TIME/UNIT

25.543 25.072 0.471

AVERAGE CONTENTS

6 .372

$AVERAGE TIME/UNIT

25.543 25.072 3 . 708

CURRENT CONTENTS

5

QTABLE NUMBER

MAXIMUM CONTENTS

9

CURRENT CONTENTS

5 5 0

--AVG-UTIL-DURING--TOTAL AVAIL UNAVL TIME TIME TIME 0.674

SYS SERV LINE

RANDOM STREAM

1

ENTRIES AVERAGE CURRENT PERCENT TIME/UNIT STATUS AVAIL

243 23.967 AVAIL 100.0

MAXIMUM CONTENTS

11 9 2

ANTITHETIC VARIATES

OFF

AVERAGE CONTENTS

6 . 098 6.067 0 . 032

INITIAL POSITION

101052

TOTAL ENTRIES

243 243 243

CURRENT POSITION

101550

PERCENT ZEROS

ZERO ENTRIES

0 0

232

SAMPLE CHI-SQUARE COUNT UNIFORMITY

498 0.63

AVERAGE CURRENT CONTENTS CONTENTS

6.067 5

AVERAGE TIME/UNIT

24.093 23.967 0.126

$AVERAGE TIME/UNIT

24.093 23.967 2 . 783

QTABLE NUMBER

MAXIMUM CONTENTS

9

CURRENT CONtENTS


8848 BYTES AVAILABLE 1152 IN USE 23 04 USED (MAX)

RELATIVE CLOCK: 960 . 0000 ABSOLUTE CLOCK: 960 . 0000


--AVG-UTIL-DURING--TOTAL AVAIL UNAVL TIME TIME TIME 0 . 640

ENTRIES AVERAGE CURRENT PERCENT CAPACITY AVERAGE CURRENT MAXIMUM TIME/UNIT STATUS AVAIL CONTENTS CONTENTS CONTENTS

229 24.138 AVAIL 100.0 9 5.758 8 9

SYS SERV LINE

RANDOM STREAM

1

MAXIMUM CONTENTS

12 9 3

ANTITHETIC VARIATES

OFF

AVERAGE CONTENTS

5 . 819 5 . 75 8 0 .061

INITIAL POSITION

101550

TOTAL ENTRIES

229 229 229

CURRENT POSITION

102021

ZERO ENTRIES

0

PERCENT ZEROS


471 0.77

AVERAGE TIME/UNIT

24.394 24.138 0 .256

$AVERAGE TIME/UNIT

24 .394 24.138 3.090

QTABLE NUMBER

CURRENT CONTENTS

135


8416 BYTES AVAILABLE 15 84 IN USE 2304 USED (MAX)

RELATIVE CLOCK : 960.0000 ABSOLUTE CLOCK: 960.0000 BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 236 11 229 2 236 12 229 3 11 EXIT 232 LN 233 14 1 5 233 15 1 6 233 7 233 8 233 9 4 233 10 229

--AVG-UTIL-DURING--TOTAL AVAIL UNAVL TIME TIME TIME

0 . 6 2 1


233 23.014 AVAIL 100.0

QUEUE

SYS SERV LINE

MAXIMUM CONTENTS

12 9 3

AVERAGE CONTENTS

5 . 674 5.586 0 .089

TOTAL ENTRIES

233 233 233

ZERO ENTRIES

0 207

PERCENT ZEROS

CAPACITY

AVERAGE TIME/UNIT

23.379 23.014 0.365


1 OFF 102021 102502 481 0.86





- -AVG--UTIL-DURING- -STORAGE TOTAL AVAIL UNAVL ENTRIES AVERAGE

SYS SERV LINE

TIME TIM 0 . 627

MAXIMUM CONTENTS

11 9 2

238 TIME/UNIT

22.757

CURRENT PERCENT STATUS AVAIL AVAIL 10 0.0

AVERAGE CONTENTS

5.681 5.642 0.039

TOTAL ENTRIES

238 238 238

ZERO ENTRIES

0 0

221

PERCENT ZEROS


1 OFF 102502 102985 483 0.57




BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 258 11 253 2 258 12 253 3 2 EXIT 254 LN 257 14 1 5 257 15 1 6 257 7 8

257 257

9 4 257 10 253

AVERAGE CONTENTS

5.586

$AVERAGE TIME/UNIT

23.379 23.014 3 .271

CURRENT CONTENTS

QTABLE NUMBER

MAXIMUM CONTENTS

9

CURRENT CONTENTS

4 4 0

AVERAGE TIME/UNIT

22.914 22.757 0 .157

AVERAGE CONTENTS

5.642

$AVERAGE TIME/UNIT

22.914 22.757 2 .198

CURRENT CONTENTS

QTABLE NUMBER

MAXIMUM CONTENTS

9

CURRENT CONTENTS

6 6


SYS SERV LINE

MAXIMUM CONTENTS

11


257 21.661 AVAIL 100.0

AVERAGE CONTENTS

5 . 823 5 . 799 0 . 024

TOTAL ENTRIES

257 257 257

ZERO ENTRIES

0

PERCENT ZEROS

AVERAGE TIME/UNIT

21 . 752 2 1 . 6 6 1 0 .091

AVERAGE CONTENTS

5 . 799

$AVERAGE TIME/UNIT

21.752 2 1 . 6 6 1 1 .802

CURRENT CONTENTS

4

QTABLE NUMBER

MAXIMUM CONTENTS

CURRENT CONTENTS

4

136

RANDOM ANTITHETIC INITIAL CURRENT STREAM VARIATES POSITION POSITION

1 OFF 102985 103503



RELATIVE CLOCK : 960.0000 ABSOLUTE CLOCK: 960.0000


SAMPLE COUNT

518

CHI-SQUARE UNIFORMITY

0.36




233 23.035 AVAIL 100.0 9 5.591 8 9

SYS SERV LINE

MAXIMUM CONTENTS

12 9 3

AVERAGE CONTENTS

5 . 648 5.591 0 . 058

TOTAL ENTRIES

233 233 233

ZERO ENTRIES

0 0

214

PERCENT ZEROS

AVERAGE TIME/UNIT

23.273 23.035 0.237

$AVERAGE TIME/UNIT

23.273 23.035 2.912

QTABLE NUMBER

CURRENT CONTENTS


1 OFF 103503 103985 482 0.95





--AVG-UTIL-DURING--TOTAL AVAIL UNAVL AVERAGE CURRENT PERCENT TIME TIME TIME TIME/UNIT STATUS AVAIL

STATIONS 0.6 95 260 23 .098 AVAIL 100.0


SYS 11 6.334 262 0 SERV 9 6.256 260 0 LINE 2 0.078 262 229 87.4


1 OFF 103985 104529 544 0.96


79 84 BYTES AVAILABLE 2 016 IN USE 23 04 USED (MAX)



AVERAGE TIME/UNIT

23.207 23 . 098 0.286

AVERAGE CONTENTS

6 .256

^AVERAGE TIME/UNIT

23.207 23.098 2.268

CURRENT CONTENTS

QTABLE NUMBER

MAXIMUM CONTENTS

9

CURRENT CONTENTS

11 9 2

137

-AVG-UTIL-DURING--STORAGE TOTAL AVAIL UNAVL CURRENT PERCENT

TIME TIME TIME TIME/UNIT STATUS AVAIL STATIONS 0. 628 228 23. 784 AVAIL 10 0.0


SYS 12 5.720 228 0 SERV 9 5.649 228 0 LINE 3 0.071 228 207 90.8


1 OFF 104529 104999 470 0.23



RELATIVE CLOCK: 960.0000 ABSOLUTE CLOCK: 960.0000 BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 248 11 238 2 248 12 238 3 5 EXIT 240 LN 246 14 1 5 246 15 1 6 246 7 246 8 246 9 8 246 10 238

AVERAGE TIME/UNIT

24.084 23.784 0.300

AVERAGE CONTENTS

5 . 649

$AVERAGE TIME/UNIT

24.084 23.784 3.258

CURRENT CONTENTS

6

QTABLE NUMBER

MAXIMUM CONTENTS

CURRENT CONTENTS

6

--AVG-UTIL-DURING--TOTAL AVAIL UNAVL CURRENT PERCENT TIME TIME TIME TIME/UNIT STATUS AVAIL CONTENTS CONTENTS CONTENTS

STATIONS 0.622 246 21, ,854 AVAIL 100.0 9 5.600 8 9

QUEUE MAXIMUM AVERAGE TOTAL ZERO PERCENT AVERAGE $AVERAGE QTABLE CURRENT QUEUE CONTENTS CONTENTS ENTRIES ENTRIES ZEROS TIME/UNIT TIME/UNIT NUMBER CONTENTS

SYS 11 5.626 246 0 21 . 957 21.957 8 SERV 9 5.600 246 0 21 .854 21. 854 8 LINE 2 0.026 246 235 95.5 0 .103 2.299 0


1 OFF 104999 105499 500 0.54



RELATIVE CLOCK: 960.0000 ABSOLUTE CLOCK: 960.0000 BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 265 11 253 2 265 12 253 3 15 EXIT 258 LN 260 14 1 5 260 15 1 6 260 7 260 8 260 9 7 260 10 253

- - AVG-UTIL-DURING- -TOTAL AVAIL UNAVL TIME TIME TIME 0 . 690


260 22.918 AVAIL 100.0

AVERAGE CONTENTS

6 .207

CURRENT CONTENTS

7

MAXIMUM CONTENTS

QUEUE

SYS SERV LINE

MAXIMUM CONTENTS

AVERAGE CONTENTS

6 .321 6.207 0.115

TOTAL ENTRIES

260 260 260

ZERO ENTRIES

0 237

PERCENT ZEROS

AVERAGE TIME/UNIT

23.341 22.918 0.423

$AVERAGE TIME/UNIT

23.341 22.918 4.782

QTABLE NUMBER

CURRENT CONTENTS

RANDOM STREAM

ANTITHETIC VARIATES

OFF

INITIAL POSITION

105499

CURRENT POSITION

106040


541 0.90


85 6 0 BYTES AVAILABLE 1440 IN USE 2416 USED (MAX)



260 260

9 9 260 10 251

138


AVERAGE TIME/UNIT

CURRENT STATUS

PERCENT AVAIL

STATIONS 0.65 6 260 21 , .804 AVAIL 100.0


SYS 11 5 . 941 260 0 SERV 9 5 . 905 260 0 LINE 2 0 . 036 260 239 91 . 9


1 OFF 106040 106569 529 0.80


82 72 BYTES AVAILABLE 172 8 IN USE 2416 USED (MAX)

RELATIVE CLOCK: 9 6 0.00 00 ABSOLUTE CLOCK: 960 . 0000 BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 251 11 242 2 251 12 242 3 5 EXIT 243 LN 25 0 14 1 5 250 15 1 6 250 7 250 8 250 9 8 250 10 242

AVERAGE TIME/UNIT

21 .938 21.804 0. 134

AVERAGE CONTENTS

5 .905

$AVERAGE TIME/UNIT

21 . 938 21.804

1 .660

CURRENT CONTENTS

9

QTABLE NUMBER

MAXIMUM CONTENTS

9

CURRENT CONTENTS

9




250 23.616 AVAIL 100.0

AVERAGE CONTENTS

6 . 150

CURRENT CONTENTS

MAXIMUM CONTENTS

9

SYS SERV LINE

MAXIMUM CONTENTS

11 9 2

AVERAGE CONTENTS

6 . 190 6. 150 0 • 041

TOTAL ENTRIES

250 250 250

ZERO ENTRIES

0 0

231

PERCENT ZEROS

AVERAGE TIME/UNIT

23.771 23.616 0.156

$AVERAGE TIME/UNIT

23.771 23 . 616 2 . 046

QTABLE NUMBER

CURRENT CONTENTS

a a

RANDOM ANTITHETIC STREAM VARIATES

1 OFF

INITIAL CURRENT POSITION POSITION

106569 107076


507 0.40





260 260

9 6 260 10 254



260 22.386 AVAIL 100.0

CAPACITY

9

AVERAGE CONTENTS

6 . 063

CURRENT CONTENTS

6

MAXIMUM CONTENTS

MAXIMUM CONTENTS

SYS SERV LINE

AVERAGE CONTENTS

6. 132 6.063 0.069

TOTAL ENTRIES

260 260 260

ZERO ENTRIES

0

PERCENT ZEROS

AVERAGE TIME/UNIT

22.642 22.386 0 .256

$AVERAGE TIME/UNIT

22.642 22.386 2 .295

QTABLE NUMBER

CURRENT CONTENTS

RANDOM STREAM

ANTITHETIC VARIATES

OFF

INITIAL POSITION

107076

CURRENT POSITION

107614

SAMPLE COUNT


0 . 08



139





RIES AVERAGE CURRENT PERCENT TIME/UNIT STATUS AVAIL

240 21.975 AVAIL 10 0.0

AVERAGE CONTENTS

5 .494

CURRENT CONTENTS

9

MAXIMUM CONTENTS

9

QUEUE

SYS SERV LINE

MAXIMUM CONTENTS

AVERAGE CONTENTS

5.551 5 .494 0 . 057

TOTAL ENTRIES

240 240 240

ZERO ENTRIES

0 228

PERCENT ZEROS

AVERAGE TIME/UNIT

22.205 21.975 0 .230

$AVERAGE TIME/UNIT

22.205 21.975 4.598

QTABLE NUMBER

CURRENT CONTENTS


1 OFF 107614 108111 497 0.72







240 23.941 AVAIL 100.0 9

AVERAGE CURRENT MAXIMUM CONTENTS CONTENTS CONTENTS

5.985 6 9

SYS SERV LINE

RANDOM STREAM

1

MAXIMUM CONTENTS

ANTITHETIC VARIATES

OFF

AVERAGE CONTENTS

6.059 5.985 0.074

INITIAL POSITION

108111

TOTAL ENTRIES

240 240 240

CURRENT POSITION

108601

ZERO ENTRIES

0

PERCENT ZEROS

AVERAGE TIME/UNIT

24.237 23.941 0.296


490 0.69

$AVERAGE TIME/UNIT

24.237 23.941 5.911

QTABLE NUMBER

CURRENT CONTENTS

6 6 0


8 704 BYTES AVAILABLE 12 9 6 IN USE 2416 USED (MAX)



STATIONS

QUEUE

--AVG-UTIL-DURING--TOTAL AVAIL UNAVL TIME TIME TIME 0. 640

SYS SERV LINE

RANDOM STREAM


235 23.517 AVAIL 10 0.0

MAXIMUM CONTENTS

ANTITHETIC VARIATES

OFF

AVERAGE CONTENTS

5.797 5.757 0.040

INITIAL POSITION

108601

TOTAL ENTRIES

236 235 236

CURRENT POSITION

109083

ZERO ENTRIES

0

SAMPLE COUNT

482

PERCENT ZEROS


0 .44

AVERAGE TIME/UNIT

23.579 23.517 0. 162


5.757 9 9

$AVERAGE TIME/UNIT

23.579 23.517 2.547

QTABLE NUMBER

CURRENT CONTENTS

10

140






QUEUE

SYS SERV LINE

MAXIMUM CONTENTS

12


233 23.116 AVAIL 100.0

AVERAGE CONTENTS

5.703 5.611 0.093

RANDOM ANTITHETIC STREAM VARIATES

1 OFF

TOTAL ENTRIES

233 233 233

INITIAL CURRENT POSITION POSITION

109083 109564

PERCENT ZEROS

ZERO ENTRIES

0 0

211


481 0.86


5.611 9 9

AVERAGE TIME/UNIT

23.498 23.116 0.381

$AVERAGE TIME/UNIT

23.498 23.116 4.038

QTABLE NUMBER

CURRENT CONTENTS






0 .682


260 22.661 AVAIL 100.0

CAPACITY AVERAGE CURRENT MAXIMUM CONTENTS CONTENTS CONTENTS

9 6.137 4 9

QUEUE

SYS SERV LINE

RANDOM STREAM

1

MAXIMUM CONTENTS

12 9 3

ANTITHETIC VARIATES

OFF

AVERAGE CONTENTS

6.214 6.137 0.077

INITIAL POSITION

109564

TOTAL ENTRIES

260 260 260

CURRENT POSITION

110096



Simulation terminated. Absolute Clock:

Total Block Executions: 58810

Blocks / second: 53464

Microseconds / Block: 18.70

ZERO ENTRIES

0 0

233

SAMPLE COUNT

532

PERCENT ZEROS


0 . 75

AVERAGE TIME/UNIT

22.946 22.661 0 .285

$AVERAGE TIME/UNIT

22.946 22.661 2.747

QTABLE NUMBER

CURRENT CONTENTS

4

Elapsed Time Used (SEC)

PASS1: SYM/XREF LOAD/CTRL: EXECUTION: OUTPUT:

TOTAL:

0 . 0 6 0.05 0 . 06 1 . 1 0 0 . 05

1 .32

GPSS/H IS A PROPRIETARY PRODUCT OF, AND IS USED UNDER A LICENSE GRANTED BY, THE WOLVERINE SOFTWARE CORPORATION, 4115 ANNANDALE ROAD, ANNANDALE, VIRGINIA 22003-2500, USA.

141

STUDENT GPSS/H RELEASE 2.01 (EP292) 30 Aug 1995 10:46:42 FILE: PROJLN.gps

LINE# STMT# IF DO BLOCK# *LOC OPERATION A,B,C,D,E,F,G COMMENTS

1 2

1 2

* *

THIS PROGRAM SIMULATES THE REFERENCE LIBRARIANS' PERFORMANCE 3 3 * IN THE LIBRARY CD-ROM LAN SYSTEM 4 5

4 5 SIMULATE

6 6 +

7 7 + AMPERVARIABLE DECLARATION 8 9

8 9 INTEGER &I

10 10 REAL &AUTI,&ULN1,&ULN2,&HLPN,&NWTH,&REFN,&NWTR 11 11 REAL &SIG,&SIG1,&SIG2,&SQA,&SQA1,&SQA2,&ASQ,&ASQ1,&ASQ2 12 12 *

13 13 * STORAGE DECLARATION 14 14 *

15 15 STORAGE S(LIBRNS),2 16 16 *

17 17 * DEFINE FUNCTIONS 18 18 *

19 19 CDHA FUNCTION RN(2) ,C9 20 20 0. ,411,5/0.721, 10/0.8 63,15/0.926,20/0.959,25/0.9 84,3 0/0.986,35 21 21 0. 995,40/1.0,50 22 22 CDHS FUNCTION RN(2) ,C12 23 23 0 . 087,1/0.499, 2/0.743,3/0.881,4/0.938,5/0.9 65,6/0.976,7/0.9 81,8 24 24 0. 989,9/0.995, ,10/0.997,11/1.0,12 25 25 REFA FUNCTION RN(3),C13 26 26 0 . 2 65,2/0.506,4/0.687,6/0.788,8/0.872,10/0.924,12/0.957, 14 27 27 0 . ,972,16/0.982,18/0.99,20/0.993,22/0.998,24/1.0,30 28 28 REFS FUNCTION RN(3),C14 29 29 0 . ,152,1/0.573, ,2/0.79,3/0.878,4/0.921,5/0.95,6/0.9 7,7/0.9 75,8 30 30 0. ,983,9/0.988, ,10/0.9 95,12/0.9 9 7,15/0.998,16/1.0,21 31 31 CLA FUNCTION RN(4),C12 32 32 0. ,267,10/0.433,2 0/0.656,30/0.744,40/0.833,50/0.9,60/0.944,70 33 33 0. ,956,10 0/0.9 67,110/0.9 78,130/0.989,170/1.0,180 34 34 CLS FUNCTION RN(4) ,C8 35 35 0. ,426,1/0.809, ,2/0.936,3/0.957,4/0.968,5/0.979,6/0.989,7/1.0,9 36 36 37 37 *

38 38 + GPSS/H BLOCKS FOR LIBRARIANS' ACTIVITIES 39 39 *

40 40 * {1} HELP CD-ROM USERS 41 41 *

42 42 1 GENERATE FN(CDHA) CD-ROM USERS NEED HELP EVERY 8.35 MIN 43 43 2 QUEUE LIBHELP 44 44 3 ENTER LIBRNS 45 45 4 TEST E F(LIBRN1),0,LBN2 SELECT LIBRN1 TO HELP CD-ROM USERS 46 46 5 SEIZE LIBRN1 AT FIRST; IF LBRN1 IS BUSY, SELECT 47 47 6 QUEUE HLPCD 48 48 7 DEPART LIBHELP LIBRN2 49 49 8 ADVANCE FN(CDHS) 50 50 9 RELEASE LIBRN1 51 51 10 DEPART HLPCD 52 52 11 TRANSFER , BK1 53 53 12 LBN2 SEIZE LIBRN2 54 54 13 QUEUE HLPCD 55 55 14 DEPART LIBHELP 56 56 15 ADVANCE FN(CDHS) 57 57 16 RELEASE LIBRN2 58 58 17 DEPART HLPCD 59 59 18 BK1 LEAVE LIBRNS 60 60 61 61 19 TERMINATE 62 62 63 63 +

64 64 * (2) HELP PATRONS AT REFERENCE DESK 65 65 66 66 20 GENERATE FN (REFA) 67 67 21 QUEUE LIBREF 68 68 22 ENTER LIBRNS 69 69 23 TEST E F(LIBRN2),0,LBN1 SELECT LIBRN2 TO DO REFERENCE AT FIRST 70 70 24 SEIZE LIBRN2 IF LIBRN2 IS BUSY, SELECT LIBRN1 71 71 25 QUEUE HLPREF 72 72 26 DEPART LIBREF 73 73 27 ADVANCE FN(REFS) 74 74 28 RELEASE LIBRN2 75 75 29 DEPART HLPREF 76 76 30 TRANSFER ,BK2 77 77 31 LBN1 SEIZE LIBRN1 78 78 32 QUEUE HLPREF 79 79 33 DEPART LIBREF 80 80 34 ADVANCE FN(REFS) 81 81 35 RELEASE LIBRN1 82 82 36 DEPART HLPREF 83 83 37 BK2 LEAVE LIBRNS

85 85 38 TERMINATE 86 86 87 87 +

88 88 * (3) ANSWER TELEPHONE CALLS 89 89 *

90 90 39 GENERATE FN(CLA) 91 91 40 ENTER LIBRNS 92 92 41 TEST E F(LIBRN2),0,LB1 93 93 42 SEIZE LIBRN2 94 94 43 QUEUE ANSPHONE 95 95 44 ADVANCE FN (CLS) 96 96 45 RELEASE LIBRN2 97 97 46 DEPART ANSPHONE 98 98 47 TRANSFER ,BK3

142

99 99 48 LB1 TEST E F(LIBRNl),0,PRMT 100 100 49 SEIZE LIBRN1 101 101 50 QUEUE ANSPHONE 102 102 51 ADVANCE FN(CLS) 103 103 52 RELEASE LIBRN1 104 104 53 DEPART ANSPHONE 105 105 54 TRANSFER ,BK3 106 106 55 PRMT PREEMPT LIBRN2 IF BOTH LIBRNS ARE BUSY, 107 107 56 QUEUE ANSPHONE 108 108 57 ADVANCE FN(CLS) INTERRUPTED AND ANSWER r

109 109 58 DEPART ANSPHONE 110 110 59 RETURN LIBRN2 111 111 60 BK3 LEAVE LIBRNS 112 112 113 113 61 TERMINATE 114 114 115 115 + TIMER SEGMENT 116 116 +

117 117 62 GENERATE 780 SIMULATE 1 DAY (13 HOURi 118 118 63 TERMINATE 1 119 119 *

120 120 * CONTROL STATEMENTS 121 121 *

122 122 DO &I = 1,2 0 REPEAT 10 TIMES 123 123 CLEAR CLEAR ALL STATISTICS 124 124 START 1 START RUN WITH PRINT 125 125 LET &AUTI=&AUTI+SR(LIBRNS) 126 126 LET &SQA=&SQA+SR(LIBRNS)*SR(LIBRNS) 127 127 LET &ULN1=&ULN1+FR(LIBRN1) 128 128 LET &SQA1=&SQA1+FR(LIBRN1)*FR(LIBRN1) 129 129 LET &ULN2=&ULN2 +FR(LIBRN2) 130 130 LET &SQA2=&SQA2+FR(LIBRN2)*FR(LIBRN2) 131 131 LET &HLPN=&HLPN+QC(LIBHELP) 132 132 LET &NWTH=&NWTH+QZ(LIBHELP) 133 133 LET &REFN=&REFN+QC(LIBREF) 134 134 LET &NWTR=&NWTR+QZ(LIBREF) 135 135 ENDDO 136 136 LET &ASQ=&AUTI+&AUTI/20. 137 137 LET &SIG=SQRT(&SQA-&ASQ)/SQRT{20*19)/l000. 138 138 LET &AUTI=&AUT1/1000/20. 139 139 LET &ASQ1=&ULN1* &ULN1/20. 140 140 LET &SIG1=SQRT(&SQA1-&ASQ1)/SQRT(20+19)/1000. 141 141 LET &ULN1=&ULN1/10 0 0/2 0. 142 142 LET &ASQ2=&ULN2 * &ULN2/2 0. 143 143 LET &SIG2=SQRT(&SQA2-&ASQ2)/SQRT(20*19)/1000. 144 144 LET &ULN2=&ULN2/10 0 0/2 0. 145 145 LET &HLPN=&HLPN/20. 146 146 LET &NWTH=&NWTH/20. 147 147 LET &REFN=&REFN/20. 148 148 LET &NWTR=&NWTR/20. 149 149 PUTPIC FILE: =ANSLN,LINES=14,(&AUTI,&SIG,&ULN1,&SIG1,&U]

LIBRN2 WILL BE

150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166

150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166

REFERENCE LIBRARIANS ACTIVITIES

AVERAGE UTILIZATIONS OF THE LIBRARIANS: STD ERROR OF AVG. UTIL. OF THE STORAGE: AVERAGE UTILIZATION OF LIBRARIAN1: STD ERROR OF AVG. UTIL. OF LIBRARIAN!: AVERAGE UTILIZATION OF LIBRARIAN2: STD ERROR OF AVG. UTIL. OF LIBRARIAN2: NUMBER OF CD-ROM USERS WHO NEED HELP: NUMBER OF THEM RECEIVED HELP WITHOUT WAIT: NUMBER OF PATRONS NEED REFERENCE: NUMBER OF THEM RECEIVED SERVICE WITHOUT WAIT:

ENTITY DICTIONARY (IN ASCENDING ORDER BY ENTITY NUMBER; => VALUE CONFLICT.)

Facilities: 1=LIBRN1 2=LIBRN2

Queues: 1=LIBHELP 2=HLPCD 3=LIBREF 4=HLPREF 5= ANS PHONE

Storages: 1=LIBRNS

Functions: 1-CDHA 2=CDHS 3=REFA 4=REFS 5=CLA

Random Numbers: 2 3 4

Integer &Vars: 1 = 1

Real &Vars: 1=ASQ 2=ASQ1 3=ASQ2 4=AUTI 5=HLPN 7=NWTR 8=REFN 9=SIG 10=SIG1 11=SIG2 13=SQA1 14=SQA2 15 =ULN1 16 =ULN2

Files: 1=ANSLN

SYMBOL VALUE EQU DEFNS CONTEXT REFERENCES BY STATEMENT NUMBER

LIBRNS 1 Absolute 15

BK1 18 59 Block 52 BK2 3 7 83 Block 76 BK3 60 111 Block 98 105 LB1 48 99 Block 92 LBN1 31 77 Block 69 LBN2 12 53 Block 45 PRMT 55 106 Block 99

6 =NWTH 12=SQA

143

LIBRN1 1 Facility 45 46 50 77 81 LIBRN2 2 Facility 53 57 69 70 74

ANSPHONE 5 Queue 94 97 101 104 107 HLPCD 2 Queue 47 51 54 58 HLPREF 4 Queue 71 75 78 82 LIBHELP 1 Queue 43 48 55 131 132 LIBREF 3 Queue 67 72 79 133 134

LIBRNS 1 15 Storage 44 59 68 83 91

CDHA 1 19 Function 42 CDHS 2 22 Function 49 56 CLA 5 31 Function 90 CLS 6 34 Function 95 102 108 REFA 3 25 Function 66 REFS 4 28 Function 73 80

2 2 Random Nmbr 19 22 3 3 Random Nmbr 25 28 4 4 Random Nmbr 31 34

I 1 9 Integer 122

ASQ 1 11 Real 136 137 ASQ1 2 11 Real 139 140 ASQ2 3 11 Real 142 143 AUTI 4 10 Real 125 125 136 136 138 HLPN 5 10 Real 131 131 145 145 149 NWTH 6 10 Real 132 132 146 146 149 NWTR 7 10 Real 134 134 148 148 149 REFN 8 10 Real 133 133 147 147 149 SIG 9 11 Real 137 149 SIG1 10 11 Real 140 149 SIG2 11 11 Real 143 149 SQA 12 11 Real 126 126 137 SQA1 13 11 Real 128 128 140 SQA2 14 11 Real 130 130 143 ULN1 15 10 Real 127 127 139 139 141 ULN2 16 10 Real 129 129 142 142 144

ANSLN 1 File 149

100 93

103 96

127 106

128 110

128 129

141 144

149 149

STORAGE REQUIREMENTS (BYTES)

COMPILED CODE: 4022 COMPILED DATA: 1944 MISCELLANEOUS: 642 ENTITIES: 1156 COMMON: 10000

TOTAL: 17664

GPSS/H MODEL SIZE: CONTROL STATEMENTS 37 BLOCKS 63

Simulation begins.


BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 89 11 75 21 147 LBN1 34 41 22 2 89 LBN2 14 22 147 32 34 42 17 3 89 13 14 23 147 33 34 43 17 4 89 14 14 24 113 34 34 44 17 5 75 15 14 25 113 35 34 45 17 6 75 16 14 26 113 36 34 46 17 7 75 17 14 27 1 113 BK2 146 47 17 8 75 BK1 89 28 112 38 146 LB1 5 9 75 19 89 29 112 39 22 49 5 10 75 20 147 30 112 40 22 50 5

BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 51 5 61 22 52 5 62 1 53 54 PRMT 56 57 58 59 BK3

0 0 0 0 0

22

LIBRN1 LIBRN2

--AVG-UTIL-DURING--TOTAL AVAIL UNAVL TIME TIME TIME 0 .378 0 .448

114 144

AVERAGE TIME/XACT

2.586 2 .429

CURRENT STATUS AVAIL AVAIL

PERCENT SEIZING PREEMPTING AVAIL XACT XACT

--AVG-UTIL-DURING--TOTAL AVAIL UNAVL ENTRIES TIME TIME TIME 0.413 258

AVERAGE CURRENT PERCENT TIME/UNIT STATUS AVAIL

2.499 AVAIL 100.0

AVERAGE CONTENTS

0.826

CURRENT CONTENTS

MAXIMUM CONTENTS

144

QUEUE

LIBHELP HLPCD LIBREF HLPREF

ANSPHONE

MAXIMUM CONTENTS

AVERAGE CONTENTS

0.013 0.290 0.017 0.492 0.044

TOTAL ENTRIES

89 89 147 147 22

ZERO ENTRIES

82 0

132 0 0

PERCENT ZEROS 92. 1

AVERAGE TIME/UNIT

0 .111 2.541 0 . 092 2 . 6 1 1 1 .575

$AVERAGE TIME/UNIT

1 .406 2 .541 0 .904 2 . 611 1 .575

QTABLE NUMBER

CURRENT CONTENTS

0 0 0 1 0

RANDOM STREAM

2 3

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION

200000 300000 400000

CURRENT POSITION

200179 300295 400045

SAMPLE COUNT

179 295 45


0 .37 0 . 85 N/A




54 PRMT


BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 51 9 61 25 52 9 62 1 53 9 63 1

57 58

25

LIBRN1 LIBRN2


117 141

AVERAGE CURRENT PERCENT SEIZING PREEMPTING TIME/XACT STATUS AVAIL XACT XACT

2.781 AVAIL 2.700 AVAIL 516

--AVG-UTIL-DURING--TOTAL AVAIL UNAVL TIME TIME TIME 0 .453


258 2.737 AVAIL 100.0

AVERAGE CONTENTS

0.905


1 2

QUEUE


ANSPHONE

MAXIMUM CONTENTS

1 2 2 2 1

AVERAGE CONTENTS

0 . 020 0.300 0 . 043 0 .541 0 .064

TOTAL ENTRIES

87 87

146 146 25

ZERO ENTRIES

72 0

121 0 0

PERCENT ZEROS 82 . 8

AVERAGE TIME/UNIT

0.177 2.693 0.231 2.891 1.988

$AVERAGE TIME/UNIT

1 .029 2 . 693 1 .346 2.891 1 .988

QTABLE NUMBER

CURRENT CONTENTS

0 0 0

RANDOM STREAM

2

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION 200179 300295 400045

CURRENT POSITION

200354 300588 400096

SAMPLE COUNT

175 293 51





0 . 83 0 . 00 N/A

BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 78 11 70 21 155 LBN1 31 41 30 2 78 LBN2 8 22 155 32 31 42 20 3 78 13 8 23 155 33 31 43 20 4 78 14 8 24 124 34 31 44 20 5 70 15 8 25 124 35 31 45 20 6 70 16 8 26 124 36 31 46 20 7 70 17 8 27 124 BK2 155 47 20 8 70 BK1 78 28 124 38 155 LB1 10 9 70 19 78 29 124 39 30 49 10 10 70 20 155 30 124 40 30 50 10

BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 51 10 61 30 52 10 62 1 53 10 63 1 54 PRMT

57 58

145

LIBRN1 LIBRN2


1 1 1 152

AVERAGE TIME/XACT

2.410 2.407


PERCENT AVAIL

SEIZING XACT

PREEMPTING XACT



263 2.408 AVAIL 100.0 2 0.812 0 2

QUEUE

LIBHELP HLPCD

LIBREF HLPREF

ANSPHONE

RANDOM STREAM

2 3

MAXIMUM CONTENTS

1 2 1

ANTITHETIC VARIATES

OFF OFF OFF

AVERAGE CONTENTS

0 . 0 1 2 0.269 0 . 023 0 .484 0.059

INITIAL POSITION

200354 300588 400096

TOTAL ENTRIES

78 78

155 155 30

CURRENT POSITION

200511 300899 400157

ZERO ENTRIES

68 0

138 0 0

SAMPLE COUNT

157 311 61

PERCENT ZEROS 87.2


0.89 0 .34 N/A

AVERAGE TIME/UNIT

0.117 2.693 0. 117 2.436 1.527

$AVERAGE TIME/UNIT

0 .916 2.693 1 .066 2.436 1.527

QTABLE NUMBER

CURRENT CONTENTS

0 0


9344 BYTES AVAILABLE 656 IN USE

1168 USED (MAX)


BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL

1 84 11 74 21 162 LBN1 36 41 22

2 84 LBN2 9 22 162 32 36 42 18

3 84 13 9 23 162 33 36 43 18

4 84 14 9 24 126 34 36 44 18

5 75 15 9 25 126 35 36 45 18

6 75 16 9 26 126 36 36 46 18

7 75 17 9 27 126 BK2 162 47 18

8 1 75 BK1 83 28 126 38 162 LB1 4

9 74 19 83 29 126 39 22 49 4

10 74 20 162 30 126 40 22 50 4

BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 51 4 61 22 52 4 62 1 53 4 63 1 54 4 PRMT 0 56 0 57 0 58 0 59 0 BK3 22

LIBRN1 LIBRN2

--AVG-UTIL-DURING--TOTAL AVAIL UNAVL TIME TIME TIME 0.350 0.448

115 153

AVERAGE CURRENT TIME/XACT STATUS

2.375 AVAIL 2.282 AVAIL

PERCENT SEIZING PREEMPTING AVAIL XACT XACT

1063



268 2.321 AVAIL 100.0 2

AVERAGE CONTENTS

0 . 798

CURRENT CONTENTS

1

MAXIMUM CONTENTS

2

QUEUE

LIBHELP HLPCD

LIBREF HLPREF

ANSPHONE

MAXIMUM CONTENTS

1 2 1

AVERAGE CONTENTS

0 . 012 0 .256 0 .011 0 .482 0 . 059

TOTAL ENTRIES

84 84

162 162 22

ZERO ENTRIES

77 0

149 0 0


AVERAGE TIME/UNIT

0.114 2.379 0.053 2.321 2. 103

$AVERAGE TIME/UNIT

1 .363 2.379 0.666 2.321 2. 103

QTABLE NUMBER

CURRENT CONTENTS

0 1 0 0 0

RANDOM STREAM

2 3

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION

200511 300899 400157

CURRENT POSITION

200680 301224 400202

SAMPLE COUNT

169 325 45


0.64 0 . 1 8 N/A



1168 USED (MAX)

146


BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 72 11 63 21 1 135 LBN1 25 41 28 2 72 LBN2 9 22 134 32 25 42 20 3 72 13 9 23 134 33 25 43 20 4 72 14 9 24 109 34 25 44 20 5 63 15 9 25 109 35 25 45 20 6 63 16 9 26 109 36 25 46 20 7 63 17 9 27 1 109 BK2 133 47 20 8 63 BK1 72 28 108 38 133 LB1 8 9 63 19 72 29 108 39 28 49 8 10 63 20 135 30 108 40 28 50 8

BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 51 1 8 61 27 52 7 62 1 53 7 63 1 54 7 PRMT 0 56 0 57 0 58 0 59 0 BK3 27

LIBRN1 LIBRN2



2.368 AVAIL 1289 2.330 AVAIL 1301

- -AVG-UTIL-DURING- -TOTAL AVAIL UNAVL TIME TIME TIME 0.352

ENTRIES AVERAGE CURRENT PERCENT CAPACITY AVERAGE TIME/UNIT STATUS AVAIL CONTENTS

234 2.345 AVAIL 100.0 2 0.704


2 2

QUEUE


ANS PHONE

MAXIMUM CONTENTS

1 1 1 2 1

AVERAGE CONTENTS

0.005 0.229 0.007 0.418 0 . 056

TOTAL ENTRIES

72 72

135 134 28

ZERO ENTRIES

0 124

PERCENT ZEROS 94.4

AVERAGE TIME/UNIT

0 .057 2.483 0 . 042 2.435 1 .562

$AVERAGE TIME/UNIT

1 . 028 2 .483 0.511 2 .435 1 .562

QTABLE NUMBER

CURRENT CONTENTS

0 0 1 1 1

RANDOM STREAM

2 3 4

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION

200680 301224 400202

CURRENT POSITION 200825 301494 400259

SAMPLE COUNT

145 270 57


0 .08 0 . 04 N/A


89 6 0 BYTES AVAILABLE 1040 IN USE 1168 USED (MAX)




--AVG-UTIL-DURING--FACILITY TOTAL AVAIL UNAVL

TIME TIME TIME LIBRN1 0.345 LIBRN2 0.467

106 164

AVERAGE TIME/XACT

2 .540 2 .223


PERCENT SEIZING PREEMPTING XACT

147


TIME TIME TIME LIBRNS 0.40 6

RIES AVERAGE TIME/UNIT

270 2.348

CURRENT STATUS AVAIL

PERCENT AVAIL 100 .0

AVERAGE CONTENTS

0.813

CURRENT CONTENTS

1

MAXIMUM CONTENTS

2

QUEUE


ANS PHONE

MAXIMUM CONTENTS

1 2 3 2

AVERAGE CONTENTS

0 .011 0.244 0.045 0.529 0.040

TOTAL ENTRIES

74 74 179 179 17

ZERO ENTRIES

161

0

PERCENT ZEROS 89.2

AVERAGE TIME/UNIT

0 . 1 2 0 2.568 0.197 2 .305 1 . 832

$AVERAGE TIME/UNIT

1.107 2.568 1 . 955 2 .305 1 . 832

QTABLE NUMBER

CURRENT CONTENTS

RANDOM STREAM

2

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION

200825 301494 400259

CURRENT POSITION

200974 301853 400294

SAMPLE COUNT

149 359 35


0 . 92 0 . 0 1 N/A



12 9 6 USED (MAX)


BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 86 11 75 21 135 LBN1 28 41 28 2 86 LBN2 10 22 135 32 28 42 21 3 86 13 10 23 135 33 28 43 21 4 86 14 10 24 107 34 28 44 21 5 76 15 10 25 107 35 28 45 21 6 76 16 10 26 107 36 28 46 21 7 76 17 10 27 1 107 BK2 134 47 21 8 1 76 BK1 85 28 106 38 134 LB1 7 9 75 19 85 29 106 39 28 49 7 10 75 20 135 30 106 40 28 50 7


LIBRN1 LIBRN2


111 138

AVERAGE TIME/XACT

2.558 2.368

CURRENT PERCENT SEIZING PREEMPTING STATUS AVAIL AVAIL

XACT 1832 1833



249 2.453 AVAIL 100.0


0.783 2 2

QUEUE


ANSPHONE

MAXIMUM CONTENTS

2 2

AVERAGE CONTENTS

0 . 028 0 .286 0 . 019 0 .445 0 . 052

TOTAL ENTRIES

86 86 135 135 28

ZERO ENTRIES

74


AVERAGE TIME/UNIT

0.256 2.594 0.109 2.569 1.458

$AVERAGE TIME/UNIT

1 .835 2.594 1 .334 2.569 1.458

QTABLE NUMBER

CURRENT CONTENTS

RANDOM STREAM

2

ANTITHETIC VARIATES

OFF OFF OFF


CURRENT POSITION

201147 302124 400351

SAMPLE COUNT

173 271 57


0 .28 0.58 N/A


9088 BYTES AVAILABLE 912 IN USE 12 9 6 USED (MAX)


BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTi 1 83 11 72 21 151 LBN1 33 41 15 2 83 LBN2 11 22 151 32 33 42 9 3 83 13 11 23 151 33 33 43 9 4 83 14 11 24 118 34 33 44 9 5 72 15 11 25 118 35 33 45 9 6 72 16 11 26 118 36 33 46 9 7 72 17 11 27 118 BK2 151 47 9 8 72 BK1 83 28 118 38 151 LB1 6 9 72 19 83 29 118 39 15 49 6 10 72 20 151 30 118 40 15 50 6

148


- -AVG--UTIL-DURING- -FACILITY TOTAL AVAIL UNAVL ENTRIES AVERAGE CURRENT PERCENT

TIME TIME TIME TIME/XACT STATUS AVAIL LIBRN1 0 .369 111 2.594 AVAIL LIBRN2 0 .415 138 2 .348 AVAIL

- -AVG--UTIL-DURING--STORAGE TOTAL AVAIL UNAVL ENTRIES AVERAGE CURRENT PERCENT

TIME TIME TIME TIME/UNIT STATUS AVAIL LIBRNS 0 .392 249 2 .457 AVAIL 100.0

QUEUE MAXIMUM AVERAGE TOTAL ZERO PERCENT


ANS PHONE

CONTENTS 1 2 3

CONTENTS 0.010 0.289 0 . 045 0.467 0 . 028

83 151 151 15

0 134

ZEROS 94.0

SEIZING XACT

PREEMPTING XACT

AVERAGE CONTENTS

0 . 785

AVERAGE TIME/UNIT

0.095 2 . 714 0.234 2 .415 1 .470

$AVERAGE TIME/UNIT

1.569 2 . 714 2.075 2 .415 1 .470

CURRENT CONTENTS

QTABLE NUMBER

MAXIMUM CONTENTS

CURRENT CONTENTS

0 0 0

RANDOM STREAM

2 3

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION

201147 302124 400351

CURRENT POSITION

201314 302427 400382

SAMPLE COUNT

167 303 31


0 .66 1 . 0 0 N/A





BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 51 6 61 21 52 6 62 1 53 6 63 1 54 PRMT 56 57 58 59 BK3

0 0

21


TIME TIME TIME LIBRN1 0.325 LIBRN2 0.384

102 137





239 2.315 AVAIL 100.0 2 0.709


0 2

QUEUE


ANS PHONE

RANDOM STREAM

MAXIMUM CONTENTS

1 2 1 2 1

ANTITHETIC VARIATES

OFF OFF OFF

AVERAGE CONTENTS

0 .006 0 .249 0 .012 0 .421 0 . 039

INITIAL POSITION

201314 302427 400382

TOTAL ENTRIES

79 79 139 139

21

CURRENT POSITION

201473 302706 400425

ZERO ENTRIES

74 0

134

SAMPLE COUNT

159 279 43

PERCENT ZEROS 93.7


0 .34 0.22 N/A

AVERAGE TIME/UNIT

0 . 057 2 .461 0 . 065 2 .365 1 .438

$AVERAGE TIME/UNIT

0 .895 2 .461 1.814 2 .365 1.438

QTABLE CURRENT NUMBER CONTENTS



129 6 USED (MAX)


149


BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 51 4 61 17 52 53 54 PRMT 56 57 58 59 BK3

62 63

4 0 0 0 0 0

17


TIME TIME TIME LIBRN1 0.381 LIBRN2 0.40 8

118 136





254 2.423 AVAIL 100.0

AVERAGE CONTENTS

0 . 789

CURRENT CONTENTS

MAXIMUM CONTENTS

2

QUEUE

LIBHELP HLPCD

LIBREF HLPREF

ANSPHONE

MAXIMUM CONTENTS

AVERAGE CONTENTS

0 . 013 0.285 0.022 0.461 0.043

TOTAL ENTRIES

87 87 150 150 17

ZERO ENTRIES

77

PERCENT ZEROS 88.5

AVERAGE TIME/UNIT

0 .116 2.555 0. 115 2.397 1 .984

$AVERAGE TIME/UNIT

1 .013 2.555 0.961 2.397 1.984

QTABLE NUMBER

CURRENT CONTENTS

RANDOM STREAM

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION

201473 302706 400425

CURRENT POSITION

201648 303007 400460

SAMPLE COUNT

175 301 35


0.89 0.59 N/A


9344 BYTES AVAILABLE 65 6 IN USE 12 9 6 USED (MAX)



BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 51 5 61 15 52 5 62 1 53 5 63 1 54 5 PRMT 0 56 0 57 0 58 59 BK3

150

LIBRN1 LIBRN2


106 118

AVERAGE TIME/XACT

2.515 2.461


PERCENT AVAIL

SEIZING XACT

PREEMPTING XACT



224 2.486 AVAIL 100.0

AVERAGE CONTENTS

0 . 714


1 2

QUEUE


ANSPHONE

MAXIMUM CONTENTS

1 2 1 2 1

AVERAGE CONTENTS

0.014 0.282 0.013 0.403 0.029

TOTAL ENTRIES

88 88

121 121 15

ZERO ENTRIES

81 0

1 1 2 0 0


AVERAGE TIME/UNIT

0.124 2.502 0.086 2.599 1 .485

$AVERAGE TIME/UNIT

1 .564 2.502 1.163 2.599 1.485

QTABLE NUMBER

CURRENT CONTENTS

0 0 0 1

RANDOM STREAM

2 3

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION

201648 303007 400460

CURRENT POSITION

201825 303250 400491

SAMPLE COUNT

177 243 31


0 .48 0 . 2 1 N/A



129 6 USED (MAX)


BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK : CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 80 11 75 21 147 LBN1 27 41 25 2 80 LBN2 4 22 147 32 27 42 20 3 80 13 4 23 147 33 27 43 20 4 80 14 4 24 120 34 27 44 20 5 76 15 4 25 120 35 27 45 20 6 76 16 4 26 120 36 27 46 20 7 76 17 4 27 1 120 BK2 146 47 20 8 1 76 BK1 79 28 119 38 146 LB1 5 9 75 19 79 29 119 39 25 49 5 10 75 20 147 30 119 40 25 50 5


--AVG-•UTIL-DURING- -FACILITY TOTAL AVAIL UNAVL ENTRIES AVERAGE CURRENT PERCENT SEIZING PREEMPTING

TIME TIME TIME TIME/XACT STATUS AVAIL XACT XACT LIBRN1 0 .296 108 2 . 139 AVAIL 3074 LIBRN2 0 .396 144 2 . 143 AVAIL 3076

- -AVG--UTIL-DURING- -STORAGE TOTAL AVAIL UNAVL ENTRIES AVERAGE CURRENT PERCENT CAPACITY AVERAGE CURRENT MAXIMUM

TIME TIME TIME TIME/UNIT STATUS AVAIL CONTENTS CONTENTS CONTENTS LIBRNS 0 .346 252 2 . 141 AVAIL 100 . 0 2 0.692 2 2

QUEUE

LIBHELP HLPCD

LIBREF HLPREF

ANSPHONE

MAXIMUM CONTENTS

1 2 1

AVERAGE CONTENTS

0 . 006 0 .236 0 . 013 0 .417 0 . 039

TOTAL ENTRIES

80 80

147 147 25

ZERO ENTRIES

75 0

136 0

PERCENT ZEROS 93.7

AVERAGE TIME/UNIT

0 .061 2 .303 0.069 2 . 2 1 1 1 .213

$AVERAGE TIME/UNIT

0.971 2.303 0.920 2 . 2 1 1 1.213

QTABLE NUMBER

CURRENT CONTENTS

0 1 0 1 0

RANDOM STREAM

2 3

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION

201825 303250 400491

CURRENT POSITION

201986 303545 400542

SAMPLE COUNT

161 295 51


0.89 0.25 N/A


90 8 8 BYTES AVAILABLE 912 IN USE

1296 USED (MAX)


151




TIME TIME TIME LIBRN1 0.368 LIBRN2 0.43 8

116 137





253 2.485 AVAIL 100.0

AVERAGE CONTENTS

0 . 8 0 6

CURRENT CONTENTS

MAXIMUM CONTENTS

QUEUE

LIBHELP HLPCD

LIBREF HLPREF

ANSPHONE

MAXIMUM CONTENTS

1 2 2 2 1

AVERAGE CONTENTS

0 . 015 0 .278 0 . 024 0 .469 0 .060

TOTAL ENTRIES

86 86 140 140 27

ZERO ENTRIES

76 0

124 0 0

PERCENT ZEROS 88.4

AVERAGE TIME/UNIT

0. 135 2.518 0 . 134 2.612 1 .722

$AVERAGE TIME/UNIT

1 .160 2.518 1 .172 2.612 1 .722

QTABLE NUMBER

CURRENT CONTENTS

0 0 0 0

RANDOM STREAM

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION

201986 303545 400542

CURRENT POSITION

202159 303826 400597

SAMPLE COUNT

173 281 55


0 . 69 0 . 93 N/A


9344 BYTES AVAILABLE 65 6 IN USE

1296 USED (MAX)


BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 86 11 73 21 1 125 LBN1 20 41 26 2 86 LBN2 12 22 124 32 20 42 18 3 86 13 12 23 124 33 20 43 18 4 86 14 12 24 104 34 20 44 18 5 74 15 1 12 25 104 35 20 45 18 6 74 16 11 26 104 36 20 46 18 7 74 17 11 27 104 BK2 124 47 18 8 1 74 BK1 84 28 104 38 124 LB1 8 9 73 19 84 29 104 39 26 49 8 10 73 20 125 30 104 40 26 50 8


- -AVG--UTIL-DURING- -FACILITY TOTAL AVAIL UNAVL ENTRIES AVERAGE CURRENT PERCENT SEIZING PREEMPTING

TIME TIME TIME TIME/XACT STATUS AVAIL XACT XACT LIBRN1 0.361 102 2. .757 AVAIL 3574 LIBRN2 0.380 134 2 .209 AVAIL 3576

--AVG-•UTIL-DURING--STORAGE TOTAL AVAIL UNAVL ENTRIES AVERAGE CURRENT PERCENT CAPACITY AVERAGE CURRENT MAXIMUM

TIME TIME TIME TIME/UNIT STATUS AVAIL CONTENTS CONTENTS CONTENTS LIBRNS 0.370 236 2 .446 AVAIL 100.0 2 0.740 2 2

152

QUEUE


ANS PHONE

MAXIMUM CONTENTS

1 2 1 2

AVERAGE CONTENTS

0.005 0.337 0.009 0 .353 0.050

TOTAL ENTRIES

86 86

125 124 26

ZERO ENTRIES

81 0

114 0 0

PERCENT ZEROS 94.2

AVERAGE TIME/UNIT

0.044 3.053 0.059 2.222 1 .509

$AVERAGE TIME/UNIT

0 .749 3 . 053 0.672 2 .222 1 .509

QTABLE NUMBER

CURRENT CONTENTS

0 2 1 0 0

RANDOM STREAM

ANTITHETIC INITIAL CURRENT SAMPLE CHI-SQUARE VARIATES POSITION POSITION COUNT UNIFORMITY

OFF 202159 202332 173 0.65 OFF 303826 304076 250 0.65 OFF 400597 400650 53 N/A


8 9 60 BYTES AVAILABLE 1040 IN USE 129 6 USED (MAX)


BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 99 11 88 21 140 LBN1 23 41 21 2 99 LBN2 10 22 140 32 23 42 14 3 99 13 10 23 140 33 23 43 14 4 99 14 10 24 117 34 23 44 14 5 89 15 10 25 117 35 23 45 14 6 89 16 10 26 117 36 23 46 14 7 89 17 10 27 117 BK2 140 47 14 8 1 89 BK1 98 28 117 38 140 LB1 7 9 88 19 98 29 117 39 21 49 7 10 88 20 140 30 117 40 21 50 7

BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 51 7 61 21 52 7 62 1 53 7 63 1 54 PRMT 56 57 58 59 BK3

LIBRN1 LIBRN2

- -AVG-UTIL-DURING- -TOTAL AVAIL UNAVL TIME TIME TIME 0.363 0.390

119 141

AVERAGE TIME/XACT

2.380 2 . 158


PERCENT AVAIL

SEIZING PREEMPTING XACT XACT 3840



260 2.260 AVAIL 100.0

AVERAGE CONTENTS

0.753


1 2

QUEUE

LIBHELP HLPCD

LIBREF HLPREF

ANSPHONE

MAXIMUM CONTENTS

1 1 2

AVERAGE CONTENTS

0 . 0 1 8 0 .290 0.033 0 .421 0 . 042

TOTAL ENTRIES

99 99

140 140

2 1

ZERO ENTRIES

91 0

124

PERCENT ZEROS 91 .9

AVERAGE TIME/UNIT

0. 146 2.286 0. 184 2 .348 1.547

$AVERAGE TIME/UNIT

1.803 2.286 1. 614 2.348 1.547

QTABLE NUMBER

CURRENT CONTENTS

0 1 0 0 0

RANDOM STREAM

2 3

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION

202332 304076 400650

CURRENT POSITION

202531 304357 400693

SAMPLE COUNT

199 2 8 1 43


0 .49 0 . 83 N/A



12 9 6 USED (MAX)



153


LIBRN1 LIBRN2


1 1 6 137


2.238 AVAIL 2.314 AVAIL 4099

- -AVG-UTIL-DURING- -TOTAL AVAIL UNAVL TIME TIME TIME 0.370


253 2.279 AVAIL 100.0


0.739 1 2

QUEUE


ANSPHONE

MAXIMUM CONTENTS

1 2 1 2 1

AVERAGE CONTENTS

0 . 004 0.253 0 .012 0 .431 0 .055

TOTAL ENTRIES

84 84

140 140 29

ZERO ENTRIES

80 0

131 0

PERCENT ZEROS 95.2

AVERAGE TIME/UNIT

0.035 2.348 0.069 2.402 1 .486

$AVERAGE TIME/UNIT

0 . 732 2.348 1 .070 2.402 1 .486

QTABLE NUMBER

CURRENT CONTENTS

0 0 0 1 0


2 OFF 202531 202700 169 0.79 3 OFF 304357 304638 281 0.53 4 OFF 400693 400752 59 N/A


9216 BYTES AVAILABLE 784 IN USE 12 9 6 USED (MAX)

RELATIVE CLOCK: 780.0 0 00 ABSOLUTE CLOCK: 780.0000



LIBRN1 LIBRN2

- - AVG-UTIL-DURING- -TOTAL AVAIL UNAVL TIME TIME TIME 0.331 0.379

1 0 1 131





232 2.390 AVAIL 100.0 2 0.711


0 2

QUEUE


ANSPHONE

MAXIMUM CONTENTS

AVERAGE CONTENTS

0.004 0.275 0.014 0.394 0.041

TOTAL ENTRIES

81 81 131 131 20

ZERO ENTRIES

79 0

1 1 8 0 0

PERCENT ZEROS 97.5

AVERAGE TIME/UNIT

0 . 037 2.651 0 . 082 2 .347 1 .617

$AVERAGE TIME/UNIT

1.518 2 . 651 0 . 823 2 .347 1 . 617

QTABLE NUMBER

CURRENT CONTENTS

0

RANDOM STREAM

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION

202700 304638 400752

CURRENT POSITION

202863 304901 400793

SAMPLE COUNT

163 263 41


0 . 18 0.31 N/A

154


9344 BYTES AVAILABLE 65 6 IN USE 129 6 USED (MAX)

RELATIVE CLOCK: 780.0000 ABSOLUTE CLOCK: 78 0.0000


BLOCK CURRENT 51 52 53 54 PRMT 56 57 58 59 BK3

TOTAL BLOCK CURRENT

62 63

0 24

TOTAL 24 1 1

LIBRN1 LIBRN2

--AVG-UTIL-DURING--TOTAL AVAIL UNAVL TIME TIME TIME 0.360 0.414

114 139


2.460 AVAIL 2.321 AVAIL 45 94


RIES AVERAGE TIME/UNIT

253 2.384

CURRENT STATUS AVAIL

PERCENT AVAIL 1 0 0 . 0

AVERAGE CONTENTS

0 . 773

CURRENT CONTENTS

1

MAXIMUM CONTENTS

2

QUEUE


ANS PHONE

MAXIMUM CONTENTS

1 2 2

AVERAGE CONTENTS

0 .010 0.294 0.021 0.434 0.045

TOTAL ENTRIES

88 88 141 141 24

ZERO ENTRIES

81 0

125 0

PERCENT ZEROS 92.0

AVERAGE TIME/UNIT

0.089 2.605 0. 114 2 .402 1 .461

$AVERAGE TIME/UNIT

1 .116 2.605 1 .003 2.402 1.461

QTABLE NUMBER

CURRENT CONTENTS

0 0 0 1 0

RANDOM STREAM

2 3

ANTITHETIC VARIATES

OFF OFF OFF

INITIAL POSITION

202863 304901 400793

CURRENT POSITION

203040 305184 400842

SAMPLE COUNT

177 283 49


0 . 6 8 0.73 N/A


9216 BYTES AVAILABLE 784 IN USE 129 6 USED (MAX)

RELATIVE CLOCK: 780.000 0 ABSOLUTE CLOCK: 780.0000

BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 1 85 11 72 21 145 LBN1 38 41 30 2 85 LBN2 13 22 145 32 38 42 23 3 85 13 13 23 145 33 38 43 23 4 85 14 13 24 107 34 38 44 23 5 72 15 13 25 107 35 38 45 23 6 72 16 13 26 107 36 38 46 23 7 72 17 13 27 107 BK2 145 47 23 8 72 BK1 85 28 107 38 145 LB1 7 9

72 19 85 29 107 39 30 49 7 10 72 20 145 30 107 40 30 50 7

BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 51 7 61 30 52 7 62 1 53 7 63 1

58 59 BK3

LIBRN1 LIBRN2


RIES AVERAGE CURRENT PERCENT SEIZING PREEMPTING TIME/XACT STATUS AVAIL XACT XACT

117 2.346 AVAIL 143 2.218 AVAIL

155

- AVG-UTIL-DURING-TOTAL TIME

AVAIL TIME

UNAVL TIME

AVERAGE TIME/UNIT

CURRENT PERCENT STATUS AVAIL

LIBRNS 0.379 260 2.276 AVAIL 100.0 2

QUEUE MAXIMUM AVERAGE TOTAL ZERO PERCENT AVERAGE QUEUE CONTENTS CONTENTS ENTRIES ENTRIES ZEROS TIME/UNIT

LIBHELP 1 0.005 85 77 90.6 0.049 HLPCD 2 0.249 85 0 2 .284 LIBREF 2 0.024 145 129 89.0 0 . 128 HLPREF 2 0.451 145 0 2 .427

ANSPHONE 1 0.058 30 0 1 .520


2 OFF 203040 203211 171 0.82 3 OFF 305184 305475 291 0.31 4 OFF 400842 400903 61 N/A

AVERAGE CONTENTS

0 . 759

$AVERAGE TIME/UNIT

0.517 2.284 1. 163 2 .427 1 .520

CURRENT CONTENTS

QTABLE NUMBER

MAXIMUM CONTENTS

2

CURRENT CONTENTS

0 0 0 0

STATUS OF COMMON STORAGE 9344 BYTES AVAILABLE 656 IN USE 129 6 USED (MAX)


BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL

1 91 11 83 21 154 LBN1 31 41 22

2 91 LBN2 8 22 154 32 31 42 15

3 91 13 8 23 154 33 31 43 15

4 91 14 8 24 123 34 31 44 15

5 83 15 8 25 123 35 31 45 15

6 83 16 8 26 123 36 31 46 15

7 83 17 8 27 123 BK2 154 47 15

8 83 BK1 91 28 123 38 154 LB1 7

9 83 19 91 29 123 39 22 49 7

10 83 20 154 30 123 40 22 50 7

BLOCK CURRENT TOTAL BLOCK CURRENT TOTAL 51 7 61 22 52 7 62 1 53 7 63 1 54 PRMT

57 58

--AVG-UTIL-DURING--ACILITY TOTAL AVAIL UNAVL

TIME TIME TIME LIBRN1 0.3 64 LIBRN2 0.454


TIME TIME TIME LIBRNS 0.409

121 146




267 2.388 AVAIL 100.0

QUEUE


ANSPHONE

RANDOM STREAM

2 3 4

MAXIMUM CONTENTS

1 2 3

ANTITHETIC VARIATES

OFF OFF OFF

AVERAGE CONTENTS

0 .018 0.257 0 . 044 0.506 0 . 054


TOTAL ENTRIES

91 91

154 154 22

CURRENT POSITION

203394 305784 400948


9344 BYTES AVAILABLE 65 6 IN USE

1424 USED (MAX)

Simulation terminated. Absolute Clock: 780.0000

Total Block Executions: 63835

Blocks / second: 555 0 9

Microseconds / Block: 18.02

Elapsed Time Used (SEC)

PASS1: PASS2: LOAD/CTRL: EXECUTION: OUTPUT:

0.11 0.11 0.17 1.15 0.28

TOTAL: 1 . 8 2

ZERO ENTRIES

82 0

135 0 0

SAMPLE COUNT

183 309 45



0.54 0.51 N/A

AVERAGE TIME/UNIT

0.154 2.201 0.223 2.564 1.927

AVERAGE CONTENTS

0 . 817

$AVERAGE TIME/UNIT

1 .554 2 .201 1 .810 2.564 1 .927

CURRENT CONTENTS

0

QTABLE NUMBER

MAXIMUM CONTENTS

2

CURRENT CONTENTS

GPSS/H IS A PROPRIETARY PRODUCT OF, AND IS USED UNDER A LICENSE GRANTED BY, THE WOLVERINE SOFTWARE CORPORATION, 4115 ANNANDALE ROAD, ANNANDALE, VIRGINIA 22003-2500, USA.

156

REFERENCE LIBRARIANS DAILY ACTIVITIES BASED ON 50 REPLICATIONS WITH 2 LIBRARIANS

AVERAGE UTILIZATIONS OF THE LIBRARIANS: 0.383 STD ERROR OF AVG. UTIL. OF THE STORAGE: 0.004 AVERAGE UTILIZATION OF LIBRARIAN1: 0.350 STD ERROR OF AVG. UTIL. OF LIBRARIAN1: 0.005 AVERAGE UTILIZATION OF LIBRARIAN2: 0.417 STD ERROR OF AVG. UTIL. OF LIBRARIAN2: 0.004 NUMBER OF CD-ROM USERS WHO NEED HELP: 84.360 NUMBER OF THEM RECEIVED HELP WITHOUT WAIT: 76.780 NUMBER OF PATRONS NEED REFERENCE: 143.360 NUMBER OF THEM RECEIVED SERVICE WITHOUT WAIT: 128.120 AVG SERVICE TIME OF HELPING CD-ROM USERS: 2.504 AVG SERVICE TIME OF REFERENCE: 2.419 NUMBER OF TELEPNOE CALLS PER DAY: 23.940 AVG TIME FOR ANSWERING A TELEPHONE CALL: 1.661

REFERENCE LIBRARIANS DAILY ACTIVITIES BASED ON 50 REPLICATIONS WITH 1 LIBRARIAN

AVERAGE UTILIZATIONS OF THE LIBRN: 0.770 STD ERROR OF AVG. UTIL. OF THE LIBRN: 0.007 NUMBER OF CD-ROM USERS WHO NEED HELP: 84.400 NUMBER OF THEM RECEIVED HELP WITHOUT WAIT: 26.140 NUMBER OF PATRONS NEED REFERENCE: 143.800 NUMBER OF THEM RECEIVED SERVICE WITHOUT WAIT: 42.800 AVG SERVICE TIME OF HELPING CD-ROM USERS: 2.651 AVG SERVICE TIME OF REFERENCE: 2.576 NUMBER OF TELEPNOE CALLS PER DAY: 25.120 AVG TIME FOR ANSWERING A TELEPHONE CALL: 1.729

SIMULATION RESULT AFTER 60 RUNS WITH 5 CD-ROM STATIONS

AVERAGE UTILIZATION OF THE STORAGE: 0.910 THE STANDARD ERROR OF AVG. UTILIZATION: 0.005 AVERAGE NUMBER OF SYSTEM USERS PER DAY: 193.000 STATION AVERAGE SERVICE TIME: 22.924 AVERAGE NUMBER OF THE USERS WITH NO WAIT: 69.150 AVERAGE WAITING TIME IN THE QUEUE: 13.612

157









158









159





Appendix D

160

161

Mann-Whitney Test Results with MINITAB

Mann-Whitney test for CD-ROM system users

(1) CD-ROM users interarrival time.

MTB > Mann-Whitney 95.0 CI C2; SUBC> Alternative 0.

Mann-Whitney Confidence Interval and Test

CI N = 4 Median = 266.00 C2 N = 20 Median = 246.00 Point estimate for ETA1-ETA2 is 21.00 95.2 pet c.i. for ETA1-ETA2 is (-11.01,58.99) W = 71.0 Test of ETA1 = ETA2 vs. ETA1 n.e. ETA2 is significant at 0.1123 The test is significant at 0.1120 (adjusted for ties)

Cannot reject at alpha = 0.05

MTB > save 'a:cduser'

Worksheet saved into file: a:cduser.MTW MTB > Stop. *** Minitab Release 8.2 *** Minitab, Inc. *** Storage available 16174

(2) The workstations service time.

MTB > Mann-whitney 95.0 cl c2; SUBC> alternative 0.


Cl N = 4 Median = 22.610 C2 N = 20 Median = 23.248 Point estimate for ETA1-ETA2 is -0.398 95.2 pet C.i. for ETA1-ETA2 is (-3.843,1.450) W = 44.0

Test of ETA1 = ETA2 vs. ETA1 n.e. ETA2 is significant at 0.6701


162

Mann-Whitney test for the CD-ROM help requests.

(1) The CD-ROM users' help requests interarrival time.

MTB > Mann-Whitney 95.0 cl c2; SUBC> Alternative 0.


Cl N = 4 Median = 90.00 C2 N = 20 Median = 85.50 Point estimate for ETA1-ETA2 is 5.50 95.2 pet C.i. for ETA1-ETA2 is (-4.99,23.00) W = 68.5 Test of ETA1 = ETA2 vs. ETA1 n.e. ETA2 is significant at 0.1632 The test is significant at 0.1622 (adjusted for ties)


MTB > save 'arcdhelp'

(2) The librarians' service time for CD-ROM users' help requests.

MTB > Mann-whitney 95.0 c3 c4; SUBC> alternative 0.


C3 N = 4 Median = 2.2400 C4 N = 20 Median = 2.5295 Point estimate for ETA1-ETA2 is -0.2380 95.2 pet C.i. for ETA1-ETA2 is (-0.4551,0.2850) W = 32.0 Test of ETA1 = ETA2 vs. ETA1 n.e. ETA2 is significant at 0.1752 The test is significant at 0.1752 (adjusted for ties)


163

Mann-Whitney test for reference requests.

(1) The reference patrons interarrival time.

MTB > Mann-Whitney 95.0 c3 c4; SUBC> Alternative 0.


C3 N = 4 Median = 154.50 C4 N = 20 Median = 141.00 Point estimate for ETA1-ETA2 is 7.50 95.2 pet c.i. for ETA1-ETA2 is (-13.00,30.00) W = 57.5 Test of ETA1 = ETA2 vs. ETA1 n.e. ETA2 is significant at 0.5877 The test is significant at 0.5868 (adjusted for ties)


MTB > Stop. *** Minitab Release 8.2 *** Minitab, Inc. *** Storage available 16174

(2) The librarians' service time for general reference.

MTB > Mann-Whitney 95.0 c5 c6; SUBC> alternative 0.


C5 N = 4 Median = 2.2050 C6 N = 20 Median = 2.4085 Point estimate for ETA1-ETA2 is -0.2240 95.2 pet c.i. for ETA1-ETA2 is (-0.4151,0.1959) W = 35.0 Test of ETA1 = ETA2 vs. ETA1 n.e. ETA2 is significant at 0.2614 The test is significant at 0.2613 (adjusted for ties)


164

Mann-Whitney test for telephone calls

(1) The telephone calls interarrival time.

MTB > Mann-Whitney 95.0 cl c2; SUBC> Alternative 0.


Cl N = 4 Median = 23.00 C2 N = 20 Median = 23.00 Point estimate for ETA1-ETA2 is 0.00 95.2 pet C.i. for ETA1-ETA2 is (-6.00,7.00) W = 51.0 Test of ETA1 = ETA2 vs. ETA1 n.e. ETA2 is significant at 0.9691 The test is significant at 0.9690 (adjusted for ties)


MTB > save 'a:calls'

Worksheet saved into file: a:calls.MTW MTB > Stop. *** Minitab Release 8.2 *** Minitab, Inc. *** Storage available 16174

(2) The service time to answer telephone calls.

MTB > Mann-Whitney 95.0 c7 c8; SUBC> alternative 0.


C7 N = 4 Median = 1.4950 C8 N = 20 Median = 1.5370 Point estimate for ETA1-ETA2 is -0.1645 95.2 pet C.i. for ETA1-ETA2 is (-0.3570,0.1791) W = 41.0

Test of ETA1 = ETA2 vs. ETA1 n.e. ETA2 is significant at 0.5103


MTB > save 'a:service' Worksheet saved into file: a:service.MTW MTB > Stop. *** Minitab Release 8.2 *** Minitab, Inc. *** Storage available 16174

APPENDIX E

165

166

GPSS/H Program for Animation

*

* THIS PROGRAM GENERATES AN ATF FILE TO ANIMATE THE PERFORMANCE * OF THE CD-ROM LAN SYSTEM IN A LIBRARY *

SIMULATE

* Proof Macros *

REAL *

PUTTIME STARTMACRO TEST NE BPUTPIC

TI * # * BLET ENDMACRO

*

CREATE STARTMACRO PUTTIME MACRO

BPUTPIC CR #A *

ENDMACRO *

DESTROY STARTMACRO PUTTIME MACRO

BPUTPIC DES *

ENDMACRO *

PLACEIN STARTMACRO PUTTIME MACRO

BPUTPIC PL * IN #B*

ENDMACRO *

PLACEON STARTMACRO PUTTIME MACRO

BPUTPIC PL * ON #B

ENDMACRO *

SETCLAS STARTMACRO PUTTIME MACRO

BPUTPIC SET * CLASS #B

ENDMACRO

&ATFTIME

AC1,&ATFTIME,*+3 FILE=ATF,(AC1)

&ATFTIME=AC1

FILE=ATF,(#B)

FILE=ATF,(#A)

FILE=ATF,(#A,#C)

FILE=ATF,(#A)

FILE=ATF,(#A)

167

ALLCDST STORAGE 9 *

* DEFINE FUNCTIONS *

ARRIV FUNCTION RN(1),C12 0.408,2/0.698,4/0.847,6/0.922,8/0.961,10/0.976,12/0.987,14 0.989,16/0.992,18/0.996,20/0.998,24/1.0,28

SERV FUNCTION RN(1),C11 0.25,10/0.548,20/0.754,30/0.87,40/0.937,50/0.967,60/0.984,70 0.993,80/0.998,90/0.999,100/1.0,150

*

* ONE-LINE, SINGLE-SERVER QUEUEING MODEL *

GENERATE FN(ARRIV) ADVANCE SEIZE DOORWAY ADVANCE 0.3 GO THROUGH THE DOORWAY RELEASE DOORWAY QUEUE QCD

CREATE MACRO waiting,XID1 PLACEON MACRO XIDl,line

ENTER ALLCDST ADVANCE 0.1 GO THROUGH THE WAITING LINE DEPART QCD SELECT MIN CDST,1,9, , F SEIZE PH(CDST) CAPTURE A CD-ROM STATION

SETCLAS MACRO XID1,customer PLACEIN MACRO XID1,chair,PH(CDST)

ADVANCE FN(SERV) RELEASE PH(CDST)

DESTROY MACRO XID1 LEAVE ALLCDST TERMINATE 1 USER LEFT

*

ATF FILEDEF 'CDROM.ATF' *

ASSIGN COUNT,10,PH *

OBSERVE ASSIGN UTIL1+,F(1),PH ASSIGN UTIL2+,F(2),PH ASSIGN UTIL3 +,F(3),PH ASSIGN UTIL4+,F(4),PH ASSIGN UTIL5+,F(5),PH ASSIGN UTIL6+,F(6),PH ASSIGN UTIL7+,F(7),PH ASSIGN UTIL8+,F(8),PH ASSIGN UTIL9+,F(9),PH ASSIGN UTIL+,S(ALLCDST),PH ADVANCE 5

168

LOOP (COUNT)PH,OBSERVE

BPUTPIC FILE=ATF,LINES=12,(AC1,_ 10*PH(UTIL1),10*PH(UTIL2),10*PH(UTIL3) 10*PH(UTIL4),10*PH(UTIL5),10*PH(UTIL6) 10*PH(UTIL7),10*PH(UTIL8),10*PH(UTIL9) 10*(PH(UTIL)/9 .),10*Q(QCD))

TIME * SET BAR UTIL1 TOP *

SET BAR UTIL2 TOP *

SET BAR UTIL3 TOP *

SET BAR UTIL4 TOP *

SET BAR UTIL5 TOP *

SET BAR UTIL6 TOP *

SET BAR UTIL7 TOP *

SET BAR UTIL8 TOP *

SET BAR UTIL9 TOP *

SET BAR UTIL RIGHT * SET BAR QUEUE RIGHT *

TERMINATE 0

START 960 SIMULATE 1 DAY (16 HOURS) END

169

An Example Screen of the Animation

APPENDIX

170

171

Variables

REGRESSION OF UTILIZATION ON NUMBER OF STATIONS

14:10 Sunday, September 10, 1995

Descriptive Statistics

Sum Mean Uncorrected SS

INTERCEP STNS UTIL

11 110

6 .768

1 10

0 . 6152727273

11 1210

4 .46415

Variables Variance Std Deviation

INTERCEP STNS UTIL

0 11

0 . 0299984182 3.3166247904 0.1732005144

Model: MODEL1 Dependent Variable: UTIL

Source

Model Error C Total

DF

1 9

10

Analysis of Variance

Sum of Squares

0.29381 0.00617 0.29998

Mean Square

0 .29381 0 . 00069

F Value

428 .362

Prob>F

0.0001

Root MSE Dep Mean C.V.

0.02619 0 .61527 4 .25658

R-square Adj R-sq

0.9794 0.9771

Parameter Estimates

Variable DF Parameter Estimate

Standard Error

T for HO: Parameter=0 Prob >

INTERCEP STNS

Variable DF

1.132091 -0.051682

Standardized Estimate

0 . 02618958 0 .00249708

43 . 227 -20 . 697

0 .0001 0 .0001

INTERCEP STNS

0 . 00000000 -0 . 98965757

Obs

REGRESSION OF UTILIZATION ON NUMBER OF STATIONS 14:10 Sunday, September 10, 1995

Dep Var UTIL

Predict Value

Std Err Predict

Lower95% Predict

Upper95% Predict Residual

Std Err Residual

1 0 . 9100 0 .8737 0 . 015 0 .8057 0 . 9417 0 . 0363 0 .022 2 0 .8420 0 .8220 0 . 013 0 .7561 0 . 8879 0 .0200 0 . . 023 3 0 . 7720 0 .7703 0 .011 0 .7062 0 .8345 0 .00168 0 . . 024 4 0 . 6990 0 .7186 0 .009 0 . 6557 0 .7815 -0 . 0196 0 . . 024 5 0 , . 6450 0 , . 6670 0 . .008 0 . . 6048 0 , .7291 -0 . 0220 0 , . 025 6 0 , .5760 0 , . 6153 0 . .008 0 , .5534 0 , . 6772 -0.0393 0 , . 025 7 0 , .5440 0 . .5636 0 , .008 0 . .5015 0 . . 6257 -0 .0196 0 . . 025 8 0 . .5030 0 . .5119 0 , .009 0 . .4490 0 . .5748 -0 . 00891 0 . . 024 9 0 . .4590 0 , .4602 0 , . Oil 0 . .3961 0 . .5244 -0.00123 0 . . 024

10 0 . .4250 0 . .4085 0 . . 013 0 , .3427 0 . .4744 0 . 0165 0 . . 023 11 0 . .3930 0 , .3569 0 . . 015 0 . . 2888 0 . .4249 0 . 0361 0 . . 022

172

Obs

1 2 3 4 5 6 7 8 9

10 11

Student Residual

679 874 071

-0 .803 -0 .884 -1.573 -0 .789 -0 .364 -0 .052

.719

. 671

- 2 - 1 - 0 1 2

* * * *

* *

ie it it *

* * * *

Cook'S D

0 . 658 0 .118 0 . 001 0 . 047 . 043 .124 . 035 .010 .000 . 0 8 0 . 652

Sum of Residuals 7.771561E-16 Sum of Squared Residuals 0.0062 Predicted Resid SS (Press) 0.0103

173

REGRESSION OF CONVERTED WAITING RATE ON NUMBER OF STATIONS 1 22:32 Monday, September 11, 1995

Variables



INTERCEP CVTST CVTWR

11 1.235 4 .46

0 .1122727273 0 .4054545455

11 0.156913

85 . 929576

Variables

INTERCEP CVTST CVTWR

Variance

0 .0018256182 8.4121248727

Std Deviation

0 .0427272534 2.9003663342

REGRESSION OF CONVERTED WAITING RATE ON NUMBER OF STATIONS 2 22:32 Monday, September 11, 19 95

Model: MODEL1 Dependent Variable: CVTWR


Source

Model Error C Total

DF

1 9

10

Sum of Squares

69 .83548 14.28577 84.12125

Mean Square

69 .83548 1.58731

F Value

43 .996

Prob>F

0 . 0001


1.25988 0 .40545

310 .73372

R-square Adj R-sq

0 .8302 0.8113

Parameter Estimates

Variable DF

INTERCEP CVTST

Variable DF

Parameter Estimate

-6 .538508 61 . 849057

Standardized Estimate

Standard Error

1.11367558 9 .32450052

T for HO: Parameter=0

-5.871 6 . 633

Prob >

0 .0002 0 .0001

INTERCEP CVTST

0 . 00000000 0 .91114019

REGRESSION OF CONVERTED WAITING RATE ON NUMBER OF STATIONS 3 22:32 Monday, September 11, 19 95

Dep Var Predict Std Err Lower95% Upper95% Std Err Obs CVTWR Value Predict Predict Predict Residual Residual

1 -4 .6050 -2 .3946 0 .568 -5 .5209 0 .7316 -2 .2104 1. .125 2 -2 .9960 -2 .1472 0 .541 -5 .2487 0 . . 9543 -0 .8488 1. .138 3 -2 .3030 -1 .7761 0 .502 -4 .8445 1, .2923 -0 .5269 1, .155 4 -1. .2040 -1. .4050 0 .468 -4 . .4452 1. . 6351 0 . .2010 1. .170 5 0 -0 . . 9102 0 .429 - 3 . . 9207 2 , .1002 0 . . 9102 1, .185 6 0 , . 6420 -0 . .3536 0 , .397 -3 . .3416 2 , . 6344 0 . .9956 1. .196 7 1 . . 6490 0 , .3267 0 , .380 -2 . .6502 3 , .3037 1, .3223 1. .201 8 2 . .3610 1. .1926 0 . .398 -1. .7963 4 . .1815 1 . .1684 1 . ,195 9 3 . .0960 2 . .3059 0 , .476 -0 . .7406 5 . .3525 0 . .7901 1 . , 167

10 3 . . 6580 3 , .7903 0 , . 636 0 , .5975 6 , . 9831 -0 . . 1323 1 . . 087 11 4 . .1620 5 , .8313 0 . .902 2 . .3262 9 . . 3364 -1 . . 6693 0 . .880

174

Obs

1 2 3 4 5 6 7 8 9

10 11

Student Residual

-1.9 65 -0 .746 -0 .456 0 .172 0 .768 0 .833 1.101 0 .977 0 . 677

-0 .122 -1.898

- 2 - 1 - 0 1 2

* * * *

* * *

Cook's D

0 .492 0 .063 0 . 020 0 . 002 0 . 039 0 . 038 0 .061 0 . 053 0 . 038 0 .003 1.893

Sum of Residuals -7.10543E-15 Sum of Squared Residuals 14.2858 Predicted Resid SS (Press) 27.9104

175

REGRESSION OF CONVERTED WAITING TIME IN THE QUEUE 1 20:27 Tuesday, September 12, 1995

Variables



INTERCEP CVTST CVTWT

11 1.235 2.536

0.1122727273 0 .2305454545

11 0 .156913

34 . 664192

Variables Variance Std Deviation

INTERCEP CVTST CVTWT

0 .0018256182 3 .4079528727

0 .0427272534 1.8460641573

Model: MODEL1 Dependent Variable:

Source


Model Error C Total

CVTWT

DF

1 9

10


Sum of Squares

24.24154 9.83798

34.07953

Mean Square

24 .24154 1.09311

F Value

22.177

Prob>F

0.0011


1.04552 0 . 23055

453 .49786

R-square Adj R-sq

0 .7113 0 . 6792

Parameter Estimates

Variable DF Parameter Estimate

Standard Error

T for HO: Parameter=0 Prob >

INTERCEP CVTST

-3.860643 36 .439731

0 .92418720 7.73796618

-4.177 4 .709

0.0024 0.0011

Variable DF Standardized

Estimate

INTERCEP CVTST

0 .00000000 0 .84339953

Obs


Dep Var CVTWT

Predict Value

Std Err Predict

Lower95% Predict

Upper95% Predict Residual

Std Err Residual

1 -3 .3240 -1 .4192 0 .471 -4 .0135 1 .1751 -1 .9048 0 . 933 2 -2 .1720 -1 .2734 0 .449 -3 . .8472 1. .3004 -0 .8986 0 . .944 3 -1 . 6930 -1 . 0548 0 .417 -3 . .6011 1. .4915 -0 . . 6382 0 . . 959 4 0 . .4800 -0 . .8361 0 . 388 -3 . .3590 1. . 6868 1 .3161 0 . . 971 5 0 . .3070 -0 . .5446 0 . 356 -3 . . 0429 1. . 9536 0 . 8516 0 . . 983 6 0 , .7290 -0 , .2167 0 , . 329 -2 , .6963 2 , .2630 0 , . 9457 0 . .992 7 0 , . 9800 0 , .1842 0 , .315 -2 , .2862 2 , . 6546 0 . .7958 0 . .997 8 1, . 1640 0 , .6943 0 . .330 -1, .7860 3 , .1747 0 . .4697 0 . .992 9 1 . • 53 00 1. .3502 0 . .395 -1, .1780 3 . .8784 0 . .1798 0 . .968

10 1. . 9240 2 . .2248 0 . .528 -0 , .4248 4 . .8744 -0 . .3008 0 . .902 11 2 . . 6110 3 . .4273 0 , . 748 0 . .5186 6 . .3360 -0 . .8163 0 . .730

176

Obs Student

Residual - 2 - 1 - 0 1 2

Cook's D

1 2 3 4 5 6 7 8 9

10 11

-2 . 041 -0 . 952 -0 . 666 1 .356 0 . 866 0 . 953 0 .798 .473 .186

-0 .333 -1.118

* * * * *

0 .531 0 .102 0 . 042 0 .147 0 . 049 0 .050 0 . 032 0 .012 0 .003 0 . 019 0 . 657

Sum of Residuals -1.02141E-14 Sum of Squared Residuals 9.8380 Predicted Resid SS (Press) 15.9129

BIBLIOGRAPHY

Adkins, Susan. (1993). CD-ROM: a review of the 1992 literature. Computers in Libraries. 13 (8),20-53.

Akeroyd, John. (1989). CD-ROM usage and prospects: an overview. Program. 23 (4),367-376.

Anders, Viki, & Jackson, Kathy M. (1988) . Online vs. CD-ROM: the impact of CD-ROM databases upon a large online searching program. Online. 12(6),24-32.

Armstrong, C. J., & Large, J. A. (1987). OST - a training package for end-users of online systems. Program. 21 (4) ,333-349.

Au, Ka-Neng, & Borisovets, Natalie. (1990). The changing LANdscape of undergraduate research: the Rutgers-Newark experience. In Linda Stewart, Katherine S. Chiang, & Bill Coons (Ed.), Public Access CD-ROMs in Libraries: Case Studies (pp. 217-233). Westport, CT: Meckler.

Banks, Jarry, & Carson, John S. (1984). Discrete-Event System Simulation. Englewood Cliffs, CO: Prentice Hall.

Baumler, J. V., & Baumler, J. L. (1975). A simulation of reserve book activities in a college library using GPSS/360. College & Research Libraries. 36(3),222-227.

Baycroft, Mike. (1990). Public access CD-ROM workstations: design and management. In Nancy Melin Nelson (Ed.), Computers in Libraries '90 Proceedings of the 5th Annual Computers in Libraries Conference (pp.3-5). Westport, CT: Meckler.

Bodtker, K., Wilson, L., & Godolphin, W. (1993). Simulation modelling to assist operational management and planning in clinical laboratories. Simulation. 60(4),247-255.

Bommer, Michael. (1975). Operations research in libraries: a critical assessment. Journal of the American Society of Information Science. 26 (3),137-139.

Brainard, Robert. (1995). CD-ROM network architecture: a primer. CD-ROM Professional. 8(11),46-50.

177

178

Breeding, M. (1993). The healthy LAN: tips and advice on the care and maintenance of CD-ROM networks. CD-ROM professional. 6(1),75-76.

Broadway, Marsha D. (1987). DIALTWIG: a mini-dialog in a controlled, microcomputer-based environment. Database. 10 (6),122-128.

Budd, John M., & Williams, Karen A. (1993). CD-ROMs in academic libraries: a survey. College & Research Libraries. 54 (6) ,529-535.

CD-ROM accessible on a Wide area network. (1988). Vine. 73(Dec., '88),15-18.

Carson, John S. (1989) . Verification and validation: a consultant's perspective. In Proceedings of the 1989 Winter Simulation Conference (pp. 552-558).

Chen, Ching-Chih. (1991) . Optical Discs in Libraries: Use and Trends. Medford, NJ: Learned Information, Inc.

Crain, Robert C., & Brunner, Daniel. (1989). Extended features of GPSS/H. In Proceedings of the 1989 Winter Simulation Conference (pp. 249-253).

Desmarais, Norman, ed. (1991). CD-ROM Local Area Networks: A User's Guide. Westport, CT: Meckler.

Dubey, Yogendra P. (1984). Resource Sharing Simulation System (RSSS): A Decision Support System for Library Resource Sharing Networks. A case Study. Ph. D. dissertation, University of Pittsburgh.

Elchesen, Dennis Raymond. (1982). Management of Reference Information Services: A Dynamic Resource Allocation and Simulation Model. Ph. D. Dissertation, University of California - Berkeley.

Elton, Martin, & Vickery, Brian. (1973). The scope for operational research in the library and information field. Aslib Proceedings. 25 (8),305-319.

Gale, J. C. (1984). Use of optical disks for information storage and retrieval. Information Technology and Libraries. 3(Dec., '84),379-382.

Glitz, B., & Yokote, Gail A. (1990). CD-ROM technology in a biomedical library. In Linda Stewart, Katherine S. Chiang, & Bill Coons (Ed.), Public Access CD-ROMs in Libraries: Case Studies (pp. 267-277). Westport, CT: Meckler.

179

Gordon, H. A. (1985). CD-ROM at ALA: where it's at? Online. 9,9.

Graves, G. T.f & others. (1987). Planning CD-ROM in the reference department. College & Research Libraries News. July '87,3 93.

Hatvany, Bela. (1987). Comparison of CD-ROM and online. Proceedings of the 11th International Online Information Meeting, London, Dec. 8-10, 1987. Oxford, Learned Information.

Haynes, Elizabeth. (1993). The evolution of a school library network: setting up a CD-ROM local area network (LAN). School Library Media Quarterly. 21(Summer, '93),253-255.

Herther, Nancy K. (1990). 1989 OCLC survey finds continuing growth in CD-ROMs and microcomputers in libraries. Laserdisc Professional. 3(3),22-24.

Herther, Nancy K. (1988) . CD-ROM year four: what have we learned? Database. 11(3),106-108.

Hines, Spencer C. (1985). OCLC's remote terminal emulation system for LS/2000. Library Hi Tech. 3 (4),7-9.

Hoover, Stewart V., & Perry, Ronald F. (1989). Simulation: A Problem-Solving Approach. New York, NY: Addison-Wesley Publishing.

James, Rob, & Parmerter, Jenny. (1987). Using simulation as a management training technique. Information and Library Manager. 7(1),3-10.

Karim, Ahmer Syed. (1992). A Simulation Evaluation of the Effects of Information Completeness in Choice Decisions. Ph.D. dissertation, Arisona State University.

Kester, Diane D. (1993). CD-ROMs: stand-alone or networked? School Library Media Quarterly. 21(2),127-128.

Kinder, J., & Preston, L. A. (1993). CD-ROM management: planning for success. CD-ROM Professional. 6(Jan. '93),24-25.

Kittle, Paul W., & Wood, Elizabeth H. (1993). Cd-ROM: the past and the future. In M. Sandra Wood (Ed.), CD-ROM Implementation and Networking in Health Sciences Libraries (pp. 45-55). New York, NY: Haworth Press.

180

Kocho, Keith. (1994). Adding multimedia to your network: can it be done? CD-ROM Professional. 7(2),111-113.

Kvanli, Alan H, Guynes, C. Stephen, & Pavur, Robert J. (1992) . Introduction to Business Statistics: A Computer Integrated Approach. 3rd ed. St. Paul, MN: West Publishing Company.

Laub, Leonard. (1986). What is CD-ROM? In Steve Lambert & Suzanne Ropiequet, CD-ROM: the New Papyrus. Redmond, WA: Microsoft Press.

Leggott, Mark. (1991). CD-ROM and LANs. In Norman Desmarais (Ed.), CD-ROM Local Area Networks: A User's Guide (pp. 1-10). Westport, CT: Meckler.

LePoer, Peter, & Mularski, Carol A. (1989). CD-ROM's impact on libraries and users. Laserdisk Professional. 2 (4),39-45.

Lewis, David W., & Plum, Terry. (1992). Husky Hoops and the University of Connecticut CD-ROM LAN. In Marshall Breeding (Ed.), Library LANs: Case Studies in Practice and Application (pp. 137-156). Westport, CT: Meckler.

Losee, Robert M. (1990). The Science of Information. San Diego, CA: Academic Press.

Main, Linda Y. (1992). Computer simulation and library management. Journal of Library Administration. 16 (4),109-130.

Main, Linda Y. (1989) . Computer Simulation Modeling and Circulation: An Exploration of Some of the Factors That Inhibit the Adoption of Computer Simulation Models in Libraries. Ph.D. dissertation, University of Illinois - Urbana.

Marks, Kenneth E., & Nielsen, Steven P. (1991). Local Area Networks in Libraries. Westport, CT: Meckler.

Martyn, J., & Vickry, B. C. (1970). The complesity of the modeling of information systems. Journal of Documentation. 26 (3),204-220.

Meredith, Jack R., & Gibbs, Thomas E. (1984). The Management of Operations. 2nd ed. New York, NY: John Wiley & Sons.

Morse, Philip M. (1968). Library Effectiveness: A system Approach. Boston: MIT Press.

181

Murphy, Brower. (1985). CD-ROM and libraries. Library Hi Tech. 3(2),21-26.

Nelson, Nancy Melin, & Desmarais, Norman. (1989). CD-ROM: an overview of the US development. Program. 23(4),377-383.

Nicholls, Paul, & Ensor, Pat. (1994). Ten significant CD-ROM development in 1993. Computers in Libraries. 14(2),48-51.

Nicholls, Paul., Sutherland, P., & Julien, C. (1994). CD-ROM titles in print 1993. CD-ROM Professional. 7(3), 125-131.

Nissley, Meta. (1992). LANs, licenses and copyright. In Norman Desmarais (Ed.), CD-ROM Local Area Networks: A User's Guide (pp. 93-103). Westport, CT: Meckler.

Osborne, M. R., & Watts, R. 0. (1977). Model construction and implementation. In M. R. Osborne, & R. O. Watts (Ed.), Simulation and Modelling. St. Luca, Queensland, Australia: University of Queensland Press.

Palinscar, Stephen F. (1986). How to simulate an online search ... a way to cope with mainframe crashes, carrier drops and other online demo misadventures. Online. 10 (5),109-115.

Perratore, Ed. (1991). Networking CD-ROMs: the power of shared access. PC Magazine. Dec.31, '91,333-363.

Peters, Charles. (1988). CD-ROM and optical technology: the user interface. In Proceedings of the National Online Meeting, New York, May 10-12, 1988 (pp. 311-314). Medford, NJ: Learned Information.

Ratkowsky, David A. (1990). Handbook of Nonlinear Regression Models. New York, NY : Marcel Dekker.

Regazzi, John J., & Hersberger, Rodney. (1976). Queues and reference service: a simulation of a library reference desk. Proceedings of the ASIS Annual Meeting 1976. Vol. 13 (39th Annual meeting), pt. 1, pp. 99, pt. 2, fiche VII- A14.

Robertazzi, Thomas G. (1990). Computer Networks and Systems: Queueing Theory and Performance Evaluation. New York, NY, Springer-Verlay. pp. 70.

182

Rouse, William B. (1979). Tutorial: mathematical modeling of library systems. Journal of the American Society for Information Science. 30(4),181-192 .

Salomon, Kristine. (1988). The impact of CD-ROM on reference departments (nationwide survey of academic libraries). RQ. 28 (2),203-215.

Schriber, Thomas J. (1991). An Introduction to Simulation Using GPSS/H. New York, NY : John Wiley & Sons.

Schriber, Thomas J. (1993) . Perspectives on simulation using GPSS. Proceedings of the 1993 Winter Simulation Conference. pp.193-198.

Shafa, Z. M. (1980). Staffing Reference Service in University Libraries: A Cost Effective Model for Administration Decisions. Ph.D. dissertation, Texas Woman's University.

Shaw, W. M. Jr. (1975). Computer simulation of the circulation system of a library. Journal of the American Society for Information Science. 26 (5),271-279.

Simmons, Peter. (1989). CD-ROM: new papyrus or passing fad? Microcomputers for Information Management. 6(4),293-301.

Slamecka, Vladimir. (1972). A selective bibliography on library operations research. In Don R. Swanson and Abraham Bookstein (Ed.), Operations Research: Implications for Libraries (pp. 152-158). Chicago, IL: University of Chicago Press.

Smith, Douglas S. & Crain, Robert C. (1993). Industrial strength simulation using GPSS/H. Proceedings of the 1993 Winter Simulation Conference (pp. 165-171).

Stephens, Irving E. (1970). Computer simulation of library operations: an evaluation of an administrative tool. Special Libraries. 61 (6),280-287.

Stewart, L., & Olsen, J. (1988). Compact disk databases: are they good for users? Online. 12 (3),48-52.

Stirling, Keith H. (1984). A micro-based emulation for online search services. Drexel Library Quarterly. 20(4),87-97.

Tenopir, Carol. (1991). Changes wrought by CD-ROM. Library Journal. 116 (21),108-110.

183

Thomas, Pauline A., & Robertson, Stephen E. (1975). A computer simulation model of library operations. The Journal of Documentation. 31(1),1-18.

Thompson, M. Keith, & Maxwell, Kimberly. (1990). Networking CD-ROMs. PC Magazine. 9(4),238.

Thornburg, Barbara J. (1992). CD-ROM and the academic reference librarian: a review of the literature. The Electronic Library. 10(4),219-221.

Trueswell, Richard W. , & Turner, Stephen J. (1979). Simulating circulation-use characteristic curves using circulation data. Journal of the American Society of Information Science. 30(2),83-87.

Tucker, S. L., & others. (1988). How to manage an extensive laserdisk installation: the Texas A & M experience. Online. 12 (3),34-46.

Vonville, H. M., & Wilson, M. C. (1993). Simulated online searching on CD-ROM a valuable education tool. Journal of Education for Library and Information Science. 34 (2) ,156-159.

Wiedemer, John David, & Boelio, David B. (1995). CD-ROM versus online. CD-ROM Professional. 8 (4),36-42.

Williams, James G. (1976). The use of simulation in designing a computer based library network. Proceedings of the ASIS Annual Meeting 1976. Vol. 13 (3 9th Annual meeting), pt. 1, pp. 94., pt.2, fiche VI-D6 .

Williams, James G., & Pope, Elspeth. (1976). Simulation Activities in Library, Communication, and Information Science. New York, NY: Marcel Dekker.

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