important_csm - qb

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Question Bank

Computer Simulation and Modeling

Class :-BEIT(A/B)

Chapter

Introdu!tion to Simulation

" Important de#initions

1. Define SimulationSimulation is the imitation of the operation of a real-world process or system overtime.

2. Define model?

A model is defined as a representation of a system for the purpose of studying the system.

$" Short Ans%er Questions

1. What is system, system environment?A system is defined as a group of o!ects that are !oined together in some regularinteraction or interdependence toward the accomplishment of some purpose .

2. What are the different components of the system?Different components of the system are as follows" #ntity, Attriute, Activity,

$. Which is the most important step in the simulation study?%alidation i.e. step no. & is the most important step in the simulation study.

'. What are the different types of model?We have (athematical, )hysical, Static, Dynamic, Deterministic, Stochastic, discrete,continuous models.

*. What is the difference etween verification and validation?+n verification we chec the correctness of woring of the system i.e. the computer program and in validation model is measured for correctness of its performance against

the real world for its ehavior

. ive three advantages of simulation?A/ 0o need to disrupt the ongoing operations of real system./ ypothesis can e tested for feasiility.3/ Saves cost in many cases.

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&. ive three disadvantages of simulation?A/ (odel uilding re4uires special training./ Simulation results are difficult to interpret.3/ 5ime consuming and costly.

6. ive difference etween deterministic and stochastic model.In deterministic model the input and output is known, while in stochasticmodel the input and output are random in nature.

&" Su'e!tie Questions

1. What is simulation? When it is appropriate? When it is inappropriate?

)g.no.$, '

2. What are the advantages and disadvantage of simulation?)g.no. *

$. What are the areas of application of simulation?

)g.no. &

'. What is system? #7plain different components of system with e7ample?

)g.no.8

*. 0ame several entities, attriutes, activities, events and state variales for the

following system" 9a/ A cafeteria 9/ A grocery Store 9c/ A :ast food restaurant

9d/ A hospital #mergency room 9e/ Automoile assemly room

)g.no. 1;

. What is model? #7plain different types of model with suitale e7ample?

)g.no. 1$

&. #7plain different steps in simulation study.

)g.no. 1'

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6. #7plain different phases of simulation.

)g.no. 16

*" +'e!tie Questions

1. Simulation of an is which of the following model?A/ static/ dynamic3/ stochasticD/ deterministic

Ans. Dynamic

2. Simulation is used inA/ (anufacturing


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*. +###=S(3S" +nstitute of #lectrical and #lectronics #ngineers" Systems, (an and3yernetics Society

. +###=3S" +nstitute of #lectrical and #lectronics #ngineers" 3omputers Society&. ++#" +nstitute of +ndustrial #ngineers6. +0:>(S=3S" +nstitute for >perations esearch and the (anagement Sciences" 3ollege

on Simulation8. S3S" Society for 3omputer Simulation1;. A(S" automated material handling systems

'


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Chapter $

Simulation E0amples" Important de#initions

1. Define Event?

An instantaneous occurrence that changes the state of a system. (uch as anarrival of a new customer!.

". Define system capacity? #he num$er of customers that may $e in the waiting line or system is knownas system capacity.

%. Define lead time? #he time gap $etween the review of the inventory and the receipt of an orderis known as lead time.


1. &hat is meant $y 'ueuing system?A 'ueuing system includes calling population, nature of arrivals, servicemechanism, system capacity and 'ueuing discipline.

". &hat is calling population? #he population of potential customers is referred to as the calling population.

%. &hat are the different types of calling populations, give eamples?

Infinite calling population ) finite calling population.

*. +ive types of 'ueuing system?ingle server and multi server 'ueuing system.

-. &hat do you mean $y inventory?It is the storage of items for use and this storage is reviewed after a fiedduration of time and then a $asic level no of items is maintained $y makinga order.


1. #7plain simulation of single server 4ueuing system for grocery store checout

3ounter.

)g.no. 2&

*


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2. What are the different events in 4ueuing system? #7plain with flow diagram.

)g.no. 2$

$. #7plain simulation of multi-server 4ueuing system.

)g.no. $*

'. #7plain simulation of inventory system.

)g.no. '*

*. #7plain simulation of 4ueuing system with relevant flow diagram.

)g.no. 2$


1. Ale aer is an e7ample ofA/ single channel 4ueue/ multi channel 4ueue3/ inventory systemD/ none of the aove

Ans.

2. ailway reservation counter hasA/ finite calling population/ infinite calling population

Ans. $. :or arrival event when server status is usy and 4ueue status non empty what is the out

come

A/ #nter 4ueue/ +mpossile3/ #nter service

Ans. A

'. :or arrival event when server status is usy and 4ueue status empty what is the outcomeA/ #nter 4ueue/ impossile3/ #nter service


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Ans. A

*. :or arrival event when server status is idle and 4ueue status non empty what is the outcome

A/ #nter 4ueue/ impossile3/ #nter service

Ans.

. :or arrival event when server status is idle and 4ueue status empty what is the outcomeA/ #nter 4ueue/ impossile3/ #nter service

Ans. 3

," umeri!al .ro'lems

1. aer is trying to determine how many Do@ens of agels to ae each day. 5he

)roaility distriution of the numer of agels customer is as follows"

0o. of customers per day" 6 1; 12 1'

)roaility ;.$* ;.$; ;.2* ;.1;

3ustomers order 1, 2, $ or ' do@en agels according to the following proaility

Distriution" 0o. of Do@en ordered=customer" 1 2 $ '

)roaility " ;.' ;.$ ;.2 ;.1

" A''reiations

1. I/0 irst in first out

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Chapter &

1eneral .rin!iples


1. Define #vent notice

A record of an event to occur at the current or some future time, along with any

associated data necessary to e7ecute the event at a minimum, the record includes the

event type and the event time.

2. Define Delay.

Duration of time of unspecified indefinite length, which is not nown until it ends.

$. Define :uture #vent list

A record of an event to occur at the current or some future time, along with any

associated data necessary to e7ecute the event at a minimum the record includes the

event type and the event time.

'. Define cloc

A variale representing simulated time, called 3B>3C.

*. Define activity

Duration of time of specified length, which is nown when it egins

. Define system state

A collection of variales that contain all the information necessary to descrie


1. What is imminent event?

5he event that is ne7t to happen is called imminent event.

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2. ow events are placed in :#B?

#vents are placed in :#B y time advance algorithm

$. What is 5erminating event?

5he event which maes defines how long the simulation will run is nown as

5erminating event.

'. ow terminating event is specified?

+t is specified y using notation 5e.

*. ive different types of world views.

#vent- scheduling, )rocess interaction, activity scanning

. What is ootstrapping?

5he method of generating an e7ternal arrival stream of is called ootstrapping.


1. #7plain all the concepts in discrete event system simulation.

)g.no. 8

2. #7plain event scheduling time advance algorithm.

)g.no. &1

$. What are the components of single channel 4ueue for grocery store e7ample?

)g.no. 1;

'. ow would you descrie 4ueuing system? ive the event scheduling algorithm

along With the snapshot showing cloc system state and :#B.

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)g.no. &1

*. Define model. System state, activity event, event list delay, cloc for Ale,

aer prolem and Dump truc prolem.

)g.no. 61

. #7plain data structures used in maintaining future event list.

)g.no.6&

&. #7plain dump truc prolem with time advance algorithm.

)g.no. 6'

6. What is the different world views used in simulation?

)g.no. &*


1. Delay is conditional wait" 5rue = :alse.

5rue

2. Activity is unconditional wait" 5rue=:alse.

5rue

$. B9t/ and BS9t/ are


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A/ activity

/ 3 activity

3/ )hase A

Ans. A

*. Activities or events that is conditional upon certain conditions eing true are

A/ activity

/ 3 activity

3/ )hase A

Ans.


1. Small grocery store has only one checout counter. 3ustomerEs arrive at this

checout counter at random from 1 to 6 minutes apart. #ach possile value of

interarrival time has the same proaility of occurrence. 5he service time

distriution is as follows"

Service time 9minutes/" 1 2 $ ' *

)roaility ;.;* ;.1; ;.2; ;.$; ;.2* ;.1;

)erform the simulation for 1; customers. >tain average writing time in the

ueue and average idle time of the server.

2. A dentist schedules all his patients for $;-minute appointments. Some of the patients tae more or less than $; minutes depending on the type of dental wor

to e done. 5he following summary shows the various categories of wor, their)roailities and time actually needed to complete the wor"

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3ategory of service 5ime e4uired )roaility of

9minutes/ 3ategory

:illing '* ;.';

3rown ; ;.1*

3leaning 1* ;.1*

#7traction '* ;.1;

3hecup 1* ;.2;

$. Simulate the dentistEs clinic for four hours and determine the average waiting

time for the )atients as well as the idleness of the doctor. Assume that all

the patients show up at the clinic e7actly their scheduled arrival time starting at 6.;; a.m. Fse the following andom numers for handling the aove

prolem"

'; 62 11 $' 2* 1& &8

>servations of past data show the following patterns in respect of interarrival

durations and service durations in a single channel 4ueuing system. Fsing the

random numer tale elow, simulate the 4ueue ehavior for a period of ;

minutes and estimate the proaility of the service eing idle and the mean time

spent y a customer waiting for service.

+nter-arrival 5ime Service 5ime

(inutes )roaility (inutes )roaility

2 ;.1* 1 ;.1;

' ;.2$ $ ;.22

;.$* * ;.$*

6 ;.1& & ;.2$

1; ;.1; 8 ;.1;

andom no 9start at 0orth- West corner and proceed along the row/

8$ 1' &2 1;

61 6& 8; $6

28 1& 11 6

*1 '; $; *2

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" A''reiations

1. :#B" :uture event list

Chapter *

Simulation So#t%are


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1$


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1. ive names of few simulation pacages.

Arena, Automod, )SS

2. What is )SS?

eneral purpose system simulation.

$. ive two criteria for selection of simulation soft wares?

A/ Do not focus on single issue.

/ #7ecution speed

'. 0ame few )SS locs.

#0#A5#, F#F#, S#+G#


1. #7plain the history of simulation software.

)g.no. 8

2. What are the criteria used for selection of simulation software.

)g.no. 88

$. Write short note on" 9i/ #7tend 9ii/ Automod 9iii/ Simula 9iv/ )SS

9v/ Simscript

)g.no. 12', 12$, 12&,112

'. What are the common features found in most simulation software?

)g.no. 1;;

*. With reference to )SS e7plain operation of all the locs used in simulation.

1'


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)g.no. 11'

. Write a program for single server 4ueue using any one of the simulation language

Hou now. ive comments for each statement.

)g.no. 11*


1. S+(FB6 is introduced y

A/ S+(FB6 3orporation/ roos automation

Ans. A

2. Simunner is developed y

A. )>(>D#B. fle7im software3. roos automation

Ans. A

$. :le7sim simulation is used forA/ Discrete event/ 3ontinuous event3/ oth A/ I /

Ans. A

'. )SS is ased on


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0one

" A''reiations

1. S)B" Simulation )rogramming languages

2. 3SB" 3ontrol and Simulation Banguage

$. SS:" Scalale Simulation :ramewor

'. A)+" Application )rogram +nterface

Chapter ,

Statisti!al Models in Simulation


1. Define e7pectation?

1


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5he mean 9e7pectation/ is a measure of the central tendency of a random variale.

2. Define variance?

5he variance is a measure of the spread of variation of the possile values of random

variale around the mean.


1. 0ame types of distriutions.

5here are two types of distriutions discrete distriutions and continuous distriutions

2. What is meant y ernoulli trial?

:or an e7periment consisting of n trials, each of which can e a success or failure. We

assign fi7ed value of 1 for success and ; for failure.

$. What is pmf?

)roaility mass function

'. What is pdf?

)roaility density function

*. What is cdf?

3umulative distriution function

. 0ame properties of )oisson process.

5hese are the properties of )oisson process

+. andom splitting

++. )ooled process

1&


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1. #7plain useful statistical models in inventory, 4ueuing, reliaility and maintenance

system.

)g.no. 1*&

2. #7plain different types of distriution.

)g.no. 1;

$. What are the different types of distriution used in simulation?

)g.no. 1;


1. :or discrete distriutions which of the following will e preferredA/ Summation/ +ntegration

Ans. A

2. :or continuous distriutions which of the following will e preferredA/ Summation/ +ntegration

Ans.

$. ernoulli distriution isA/ discrete/ continuous

Ans. A

'. Which of the following is not a discrete distriutionA/ ernoulli/ )oisson3/ inomialD/ amma

Ans. D

*. Which of the following is not a continuous distriution

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A/ amma/ eta3/ 0ormalD/ ernoulli

Ans. D


1. An industrial chemical that will retard the spread of fire in paint has een

Developed the local sales representative has determined, from past

e7perience, that '6J of the sales calls will result in an order.

9a/ What is the proaility that the first order will come on the fourth sales call of the

day? 9/ +f eight sales calls are made in a day, what is the proaility of receiving e7actly

Si7 orders?

9c/ +f four sales calls are made efore lunch, what is the proaility that one or less

results in an order? K

2. 5he aws are currently winning 0.55 of their games. 5here are * games in the ne7t

two wees. What is the proaility that they will win more games than they lose?

$. Arrivals at a an tellerKs cage are )oisson distriuted at the rate of 1.2 per minute

9a/ What is the proaility of @ero arrivals in the ne7t minute?

9/ What is the proaility of @ero arrivals in the ne7t 2 minutes?

'. 5he lifetime, in years of a satellite placed in orit is given y the following )D:"

:97/ L;.'e-;.'7 7ML;

:97/ L ; otherwise

9a/ What is the proaility that this satellite is still NaliveN after * years?

9/ What is the proaility that the satellite dies etween $ and years from the

time it is placed in orit?

" A''reiations

18


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0one

Chapter

Queuing Models


2;


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1. Define ueue ehavior ueue ehavior refers to the actions of customers while in a 4ueue waiting for service to egin.

2. Define ueue discipline.ueue discipline refers to the logical ordering of customers in a 4ueue and determines which

customer will e chosen for service when a server ecomes free.


1. What is Cendall notation?A==c=0=C A" inter arrival O time distriution." service-time distriutionc" numer of parallel servers 0" system capacity

C" si@e of calling population

2. ive long run measures of ueuing system. Bong run measures of ueuing system are as follows.

A/ 5ime-Average 0umer in System 9B// Average 5ime Spent in system )er 3ustomer 9w/3/ 5he 3onservation #4uationD/ Server Ftili@ation

$. ive conservation e4uation.

BL Pw


1. #7plain all the characteristic of 4ueuing system.

)g.no. 2;2

2. What are the long run measures of performance of 4ueuing system?

)g.no. 2;6

$. #7plain steady state ehavior of infinite population (orovian model represented y

(==1 and (=(=1.

)g.no. 221

'. ow would you determine cost in 4ueuing system?

)g.no. 216

*. #7plain steady state ehavior of finite population model.

)g.no. 2$*

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. #7plain 0etwor of 4ueues.)g.no. 2$8


1. QAE in Cendall notation indicatesA/ Service time/ +nter arrival time3/ 0o of parallel serversD/ 3alling population#/ System capacity

Ans"

2. QCE in Cendall notation indicatesA/ Service time

/ +nter arrival time3/ 0o of parallel serversD/ 3alling population#/ System capacity

Ans" D

$. QE in Cendall notation indicatesA/ Service time/ +nter arrival time3/ 0o of parallel serversD/ 3alling population#/ System capacity

Ans" A

'. Q0E in Cendall notation indicatesA/ Service time/ +nter arrival time3/ 0o of parallel serversD/ 3alling population#/ System capacity

Ans" #

*. Q3E in Cendall notation indicatesA/ Service time/ +nter arrival time3/ 0o of parallel serversD/ 3alling population#/ System capacity

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Ans. 3

. +n (=(=1 ueue calling population isA/ :inite / +nfinite

Ans.


1. Arrivals to an airport are all directed to the same, runway, at a certain time of. the

day, these arrivals form a )oisson process with rate $; per hour. 5he time to land

an Aircraft is a constant 8; seconds. Determine B, W, B and w for this airport. +f

a delayed aircraft ums R*;;; worth of fuel per hour on the average, determine

the average cost per aircraft of delay waiting to land..

" A''reiations

0one

Chapter 2

3andom 4um'er 1eneration


2$


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1. Define un.A run is defined as a succession of similar events, preceded and followed y a different event.


2. ive properties of random numers.andom numers have two statistical properties" uniformity and independence.

$. 0ame two techni4ues of generating random numers.A/ Binear 3ongruential (ethod/ 3omined linear congruential generator

'. What are the tests for random numers?

:re4uency tests)oer test

Autocorrelation test


1. What is random numer? State the properties of random nos. What are the prolems or

errors that can occur when generating random no.

)g.no.2*1

2. (ention properties of random nos. and give the methods of generating )seudo

andom nos.

)g.no. 2*'

$. #7plain are the test used for checing Fniformity of random no.?

)g.no. 21


1. Fniformity is the property of the random nos.A/ 5rue/ :alse

Ans. 5rue

2. Which of the following is the test for independence?A/ :re4uency test/ )oer test3/ uns testD/ 0one of the aove.

2'


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Ans. 3

$. Which of the following is the test for uniformity?A/ :re4uency test

/ )oer test3/ uns testD/ 0one of the aove.

Ans. A

'. Which test is used when no. of oservations are less than *;?

A/ 3hi Os4uare test/ C-S test3/ un length test

Ans.

*. 5he value of %ariance for uniformly distriuted isA/ 1=2/ 1=$3/ 1=D/ 1=12

Ans. D


1. 3onsider the following se4uence of random no-show would you test it for

independence.

;.12 ;.;1 ;.2$ ;.26 ;.68 ;.$1 ;.' ;.26 ;.$$ ;.8$

;.$8 ;.1* ;.$$ ;.$* ;.81 ;.'1 ;.; ;.2* ;.** ;.66

2. Fse the chi-s4uare test with a L ;.;*, to test whether the data shown elow are

uniformly distriuted.

;.$' ;.8; ;.2* ;.68 0.87 ;.'' ;.12 ;.21 ;.' ;.&

;.6$ ;.& ;.&8 ;.' ;.&; ;.61 ;.8' ;.&' ;.22 ;.&' ;.8 ;.88 ;.&& ;.& ;.* ;.'1 ;.*2 ;.&$ ;.88 ;.;2 ;.'& ;.$; ;.1& ;.62 ;.* ;.;* ;.'* ;.$1 ;.&6 ;.;* ;.&8 ;.&1 ;.2$ ;.18 ;.62 ;.8$ ;.* ;.$& ;.$8 ;.'2

2*


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$. Fse the linear congruential. method to generate a se4uence of three two-digit random

integers. Bet o L 2&, a L 6 ,c =47 and m L1;;.

'. Fse the multiplicative congruential method to generate a se4uence of four three-digit

random integers. Bet o L 11&, a L '$ and m L 1;;;.

*. 5he se4uence of numers ;.*', ;.&$, ;.86, ;.11 and ;.6 has een generated. Fse the

Colmogorov-Smirnov test with TL ;.;* to determine if the hypothesis that the

numers are uniformly distriuted on the interval U;, 1V can e re!ected.

enerate enough values in each case to complete a cycle.

. consider the, first 1; two digit .values in #7ample *. ased on runs up and runs down,

determine whether the hypothesis of independence can e re!ected, where TL ;.;*.

" A''reiations

0one

Chapter 5

3andom 6ariate 1eneration

2


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0one


1. 0ame different techni4ues of generating random variate.

A/ +nverse- 5ransform 5echni4ue

/ Acceptance- e!ection 5echni4ue

2. What do you mean y random variate?

andom variate is used to generate many of the important continuous and discretedistriutions.


1. ow would you generate random variates for the e7ponential distriution?

)g.no. 2&$

2 ow would you generate random variates from 5riangular Distriution?

)g.no. 2&6

$. #7plain different techni4ues of generating random variates.

)g.no. 268

'. What is )oisson process? #7plain characteristics of )oison process.

)g.no. 28$

*. State the distriutions which can e sampled using N+nverse transform techni4ue, write

the procedure for sampling.

)g.no. 2&$

. #7plain Acceptance re!ection techni4ue.

)g.no. 268


1. andom variate for e7ponential distriution is

2&


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A/ iLln 91- i// iL -1=P9ln 91- i//

Ans.

2. Acceptance O e!ection 5echni4ue is used forA/ enerating random numer / enerating random variate3/ 5esting random variate generator

Ans.

$. andom variate for Fniform distriution is

A/ iLln 91- i/

/ iL -1=P9ln 91- i//3/ L a X 9-a/

Ans. 3


1. Develop random variate for e7ponential distriution and uniform distriution using

inverse transform techni4ue.

2. Develop random variate for )oisson distriution using acceptance re!ection techni4ue

" A''reiations

1. 0S))" 0on stationary )oisson )rocess

2. +55" +nverse 5ransform 5echni4ue

Chapter 7

Input Modeling

26


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0one


1. 0ame the techni4ues used for identifying the distriution with data.A/ istograms/ uantile O uantile )lot

2. 0ame the techni4ues used for identifying the distriution without data.A/ #ngineering data/ #7pert option3/ )hysical or conventional limitationsD/ 5he nature of the process

$. ive e7ample of (ultivariate input model.+nventory system

'. ive e7ample of 5ime- series input model.Stoc maret transactions

*. Why goodness of fit test is used.oodness of fit tests provide helpful guidance for evaluating the suitaility of a potentialinput model.

&" Su'e!tie Questions1. Discuss steps involved in development of a model of input data.

)g. no. $;&

2. ow would you select input model without data.

)g. no. $$*

$. #7plain multivariate and time series input model.

)g. no. $$&

'. Site an e7ample where lead time and demand are not independent random variales

develop a suitale model for such a case.

)g. no. $$8

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* .ow would you collect data which is to e used as input to simulation model.

)g. no. $;6

. +n case there is no data ut the distriution is nown then, how would you generate

samples to e used as input to simulation model? enerate one set of samples inputs

using each of the method.

)g. no. $$*

&. Discuss the methods y which chosen distriution is evaluated for goodness of fit test.

)g. no. $2&


1. 5est used for evaluation of chosen distriution isA/ :re4uency test/ uns test3/ oodness of fit test

Ans. 3

2. Distriution used to model the numer of independent event that occur in a fi7edamount of time is

A/ )oisson/ 0ormal3/ inomial

Ans. A

$. Distriution used to model processes that can e viewed as sum of severale7ponentially distriuted processes.

A/ )oisson/ 0ormal3/ inomialD/ #rlang

Ans. D

'. Distriution used to model the time to failure for componentsA/ 0ormal

$;


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/ inomial3/ #rlangD/ Weiull

Ans. D

*. Which of the following is the e7ample of (ultivariate input modelA/ +nventory system/ Stoc maret transactions

Ans. A


1. ecords pertaining to the monthly numer of !o related in!uries at an underground

coal mine were eing studied y a federal agency .5he values for the past 1;;

months are as follows"

+n!uries per month" ; 1 2 $ ' *

:re4uency of occurrence" $* '; 1$ ' 1 1

Apply 3hi s4uare test to test these data to test the hypothesis that the underlying

Distriution is )oisson 9use TL;.;* 2L*.88/

" A''reiations

1. A91/" Autoregressive order- 1 model2. #A91/" #7ponential Autoregressive order- 1 model$. 0>5A" 0ormal to anything transformation

1.

Chapter 8

6eri#i!ation and 6alidation o# simulation model

$1


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1. Define verification.

%erification is the process of uilding the model correctly and implementing it with good

input and structure.

2. Define validation.

+t is the process of uilding the correct model, and accurate representation of the real

system.


1. ive difference etween verification and validation.

%erification involves correctness of model while validation checs the ehavior of the

system compared with the real world system.

2. What is 3aliration?

3aliration is the iterative process that ad!usts or alters the models and its parameters to

est fit real system ehavior.

$. ive 0yler-:inger $ step approach.

Step 1-uild a model that has high face validity.Step 2-%alidate model assumptions.Step $-3ompare the model input O output transformations to corresponding input- output

5ransformations for the real system.


1 ow would you validate simulation model?

)g .no.$1

2. #7plain the difference etween verification and validation of simulation model.

)g .no. $**

$. #7plain $ step 0ylor and :inger approach for validation.

)g .no. $2

$2


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'. Discuss causes of errors in simulation. ow will you carry out verification of

simulation?

)g .no. $*


1. 5esting whether 3onceptual model is reflected accurately in operational model ornot is nown as

A/ verification/ validation3/ caliration

Ans. A

2. 5he process of comparing the model and its ehavior to the real system and its ehavior is nown as

A/ verification/ validation3/ caliration

Ans.

$. 0ylor and :inger approach is used forA/ verification

/ validation3/ caliration

Ans.


0one

" A''reiations

1. A%" Automated guided vehicles2. +3" +nteractive un 3ontroller

Chapter

+utput Anal9sis #or a Single Model

$$


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0one


1. 0ame types of simulation with respect to output analysis.

5erminating and Steady-state simulation.

2. What are the measures of performance?

)oint estimation and interval estimation.

$. What is uantile?

uantiles descries the level of performance that can e delivered with a given proaility p.


1. #7plain types of simulation with respect to output analysis.

)g .no. $88

2. #7plain point estimator and interval estimator.

)g .no. ';&

$. What are the measures of performance and interval estimation for output analysis?

)g .no. ';8

'. #7plain output analysis for steady state simulation.)g .no. '16


1. Steady state simulation is also nown asA/ 5erminating simulations/ 0on- 5erminating simulations3/ oth of the aove.D/ 0one of the aove.

Ans.

$'


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2. >ther name for uantile isA/ +nterval/ Delay3/ eplication

D/ )ercentile

Ans. D

$. eplication method can e used for Steady- State simulations. 5rue= :alse.

Ans. 5rue.


1. 3onsider an 9(, B/ inventory system, in which the procurement 4uantity, , is defined y

L (-+, if +YB

L ; , if +MLB

where + is the level of inventory on hand plus on order at the end of a month , ( is the ma7imum

inventory level , and B is the reorder point. Since ( and B are under management control, the pair 9(, B/

is called the inventory policy. Fnder certain conditions, the analytical solution of such a model is

possile, ut the computational effort may e prohiitive. Fse simulation to investigate an 9(, B/inventory system with the following properties. 5he inventory status is checed at the end of each month.

acordering is allowed at a cost of R' per item short per month. When an order arrives, it will first e

used to relieve the acorder. 5he lead time is given y a uniform distriution on the interval 9;.2*, 1.2*/

months. Bet the eginning inventory level stand at *; units, with no orders outstanding. Bet the holding

cost e R1 per unit in inventory per month. Assume that the inventory position is reviewed each month. +f

an order is placed, its cost is R;XR*, where R; is the ordering cost and R* is the cost of each item. 5he

time etween demands is e7ponentially distriuted with a mean of 1=1* month. the si@es of the demands

follow the distriution"

Demand )roaility

1 1=2

$*


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2 1='

$ 1=6

' 1=6

9a/ (ae four independent replications, each of run length 1;; months preceded y a 12-monthinitiali@ation period. for the 9(, B/ L 9*;, $;/ policy. #stimate long Orun mean monthly cost with a 8;J

confidence interval.

9/ Fsing the results of part 9a/, estimate the total numer of replications needed to estimate mean

monthly cost within R*.

" A''reiations

0one

Chapter $

Comparison and Ealuation o# Alternatie S9stem esign

$


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1. Define (onotonicity.

5he increasing and decreasing nature of the response variales with respect to

the input random variales is nown as monotonicity.

2. Define se4uential sampling scheme.

A Se4uential sampling scheme is one in which more and more data are

collected until an estimator with a prespecified precision is achieved , or until

one of several alternative hypothesis is selected., with the proaility of

correct selection eing larger than a prespecified value.


1. Disadvantages of onferroni approach.

onferroni approach gives the increased width of each individual interval for large numer of

comparisons

2. Advantages of onferroni approach.

onferroni approach holds whether the models for the alternative designs are run with

independent sampling or with common random numers.

$. What is 3orrelated Sampling

When same data is used to simulate oth alternative system designs it is nown as

3orrelated Sampling.

'. What is other name of 3orrelated Sampling?

3orrelated Sampling is also nown as the Qcommon random- numer techni4ueE.


1 #7plain onferroni approach to multiple comparisons.

)g .no. '6

2. What is meta modeling? #7plain simple linear regression method.

)g .no. '&

$&


38/41

$. #7plain the test of significance of regression .

)g .no. '61

'. What does Zoptimi@ation via simulation Zmean?

)g .no. '6*

*. Why is optimi@ation via simulation difficult?

)g .no. '66

. Write short note on 9a/ %erification of simulation model 9/ >ptimi@ation via simulation

)g .no. '6*


1. 3orrelated sampling is also nown as common random techni4ue" 5rue=:alse.


1.Suppose that demand for a certain product has a )oisson distriution with mean 1; units. Fse

optimi@ation Ovia-simulation software9or the random-search algorithm, if you do not have access

to such software / to determine the order si@e 7 that ma7imi@es the proaility that demand

e4uals 7 units, assuming that ;YL 7YL 1;;, and 7 is an integer. Uint " >n each replication of

the simulation for a trial value of 7, a random demand is generated from the )oisson distriution

with mean 1;. if this random demand e4uals 7 , then the response is H97/ L1 otherwise it is

H97/L;.V

" A''reiations

1. 30" 3ommon random numers

2. (S" (aterials handling system

$. B0" Bi4uified 0atural as

Chapter &

Case studies


$6


39/41

0one

$" Short Ans%er Questions 0one


1. Discuss various issues in manufacturing and material handling system.

)g .no. *;6

2. What are the o!ectives in material handling simulation?

)g .no. *;&

$. ive loc diagram and e7plain se4uence of operations.

)g .no. *;*

'. #7plain simulation of computer system 93)F and (emory simulation/.

)g .no. *28

*. #7plain simulation of supermaret.

)g .no. *1*

. #7plain simulation of manufacturing and material handling system.

)g .no. *;6


0one


1; Fsing any simulator or language you lie, model some aspect of your local computing-system environment O e.g., the print 4ueue for a networ printer. 3arefully descrie yourworload model.

" A''reiations

1. AS=S" Automated storage and retrieval systems

2. W+)" wor in process

$. S(" storage retrieval machines

'. 55:" time to failure

*. 55" time to repair

. (55:" mean time to failure

$8


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&. (55" mean time to repair

6. ABF" Arithmetic logic unit8. 35(3" continuous (arov chain1;. 3)F" central processing unit11. ())" (odulated )oisson )rocess

12. +B)" +nstruction level parallelism1$. BF" Beast ecently Fsed

1'. 53)" 5ransmission control protocol1*. (A3" media access control1. 3S(A=3D" 3arrier Sense (ultiple Access= 3ollision Detection1&. #D" andom #arly Detection16. 55" round trip time18. D(B" Domain (odeling Banguage2;. 0+" 0etwor- ost- +nterface

3e#eren!es

1/ Discrete-event system simulation !erry ans, 3arson, !ohn s., fourth edition. ,)+2/ www.wintersim.org.

';

http://www.wintersim.org/http://www.wintersim.org/


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$/ www.informs-cs.org=wscpapers.html.

'1

important_csm - qb

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