optex mathematical modeling system

FICO™ XPRESS-MOSEL

CPLEX-OPL-ODM

IMPRESS

Why do you choose to programming in any specific optimization technology when you

can program in all tools at the same time with

only one effort ?

http://www.gnu.org/graphics/agnuhead.html

http://www.python.org/

Why do you choose to programming in any specific optimization technology when you

can program in all tools at the same time with

only one effort ?

The best way is to have the mathematical models in a meta-

platform, like OPTEX, and in a second phase

go to any specific commercial platform.

ALGEBRAIC LANGUAGE

MATHEMATICAL MODELERS

OPTIMIZATION LIBRARY

E R P

DB2

ORACLE EXCEL DBF

MySQL ...

ODBC

CPLEX

CLOUD

FICO™ XPRESS

OPL

FICO™ MOSEL

SPECIAL SYSTEMS

ODM

IMPRESS

http://www.gnu.org/graphics/agnuhead.html

As a part of its process of technological innovation,

DW has developed an optimization technology

called

OPTEX

Mathematical Modeling System

which is oriented to designing, implementing

and setting up large scale optimization

models for the real word .

OPTEX IS A META-FRAMEWORK

ORIENTED TOWARDS THE DESIGN, IMPLEMENTATION AND SETUP OF DECISION SUPPORT SYSTEMS BASED IN MATHEMATICAL PROGRAMMING

WITH SPECIAL EMPHASIS IN THE DEVELOPMENT OF FINAL USER APPS:

ALGEBRAIC FORMULATION IS INDEPENDENT FROM ANY PROGRAMMING LANGUAGE

CAN BE CONNECTED WITH ANY DATA SERVER

THEREBY GENERATING APPS USING MULTIPLE COMMERCIAL OR NONCOMMERCIAL TECH ACCORDING TO CLIENTS’ NEEDS

OPTEX Mathematical Modeling System, was developed to support DecisionWare’s mathematical modeling

projects since 1991.

OPTEX dramatically simplify the developing and solving

of complex optimization applications by supporting :

Rapid Prototyping Big Data Intensive Optimization

Decision-Making under Uncertainty Integrate Multiples Optimization Technologies

SUPPORTS ALL STAGES OF THE

MATHEMATICAL MODELING PROCESS


REAL WORLD

DSS

DATABASE


ALGEBRAIC MODEL DATA MODEL

MODELERS

REAL WORLD

DECISION MAKERS

G.R.G.

0-1

BALAS-BENDERS

LAGRAGIAN

RELAXATION

BENDERS THEORY

BRANCH &

BOUND

P.L.

FLUJO EN

REDES

G.R.G.

/PC

G.R.G.

/PL

D.F.P.

x, p

OPTIMIZATION SOLVER

DSS

DATABASE

DSS

DATABASE

NUMERICAL MODEL


MATRIX GENERATION


DECISION MAKERS

MODELERS

REAL WORLD

G.R.G.

0-1

BALAS-BENDERS

LAGRAGIAN

RELAXATION

BENDERS THEORY

BRANCH &

BOUND

P.L.

FLUJO EN

REDES

G.R.G.

/PC

G.R.G.

/PL

D.F.P.

x, p

OPTIMIZATION SOLVER

DSS

DATABASE

DSS

DATABASE

NUMERICAL MODEL


MATRIX GENERATION


DECISION MAKERS

MODELERS

REAL WORLD

THIRD PART PROVIDER

G.R.G.

0-1

BALAS-BENDERS

LAGRAGIAN

RELAXATION

BENDERS THEORY

BRANCH &

BOUND

P.L.

FLUJO EN

REDES

G.R.G.

/PC

G.R.G.

/PL

D.F.P.

x, p

OPTIMIZATION SOLVER

DSS

DATABASE

DSS

DATABASE

NUMERICAL MODEL


MATRIX GENERATION


DECISION MAKERS

MODELERS

REAL WORLD

MAY BE THIRD PART PROVIDER

MODELERS

REAL WORLD

ALGEBRAIC MODEL

DECISION MAKERS

DEVELOPING MATHEMATICAL

MODELS

MODELERS

REAL WORLD

ALGEBRAIC MODEL

DECISION MAKERS

OPL

FICO™ MOSEL

OPTIMIZATION TECHNOLOGY


MODELS

TRADITIONAL WAY

PROGRAMMERS

DSS

DATA BASE

DATA MODEL

PROGRAMMING

DSS

DATA BASE

DATA MODEL

MODELERS

REAL WORLD

ALGEBRAIC MODEL

DECISION MAKERS

OPL

FICO™ MOSEL

OPTIMIZATION TECHNOLOGY


MODELS

OPTEX WAY

FILLING THE BLANKS

CODE GENERATION

A DECISION SUPPORT SYSTEM

IS AS A DECISION MAKING CHAIN INTEGRATED BY A COLLECTION

OF MODELS AND DATA FLOW

PTA Industrial Operations

Tactical Planning

DEM Long/Medium/Short

Demand Planning INV

Inventory Policy

Medium / Short Term Demand Projections

Inventory Policy

Production Goals

POD Production Schedule

DIS Distribution

Schedule

Distribution Goals

PCO Sourcing

Sourcing Goals

Production Orders

Distribution Orders

Sourcing Orders

PES Supply Chain Design

Short / Medium Term Market Scenarios

Expansion Plans

DSS

Short / Medium Term Market Scenarios


Tactical Planning


Demand Planning

INV Inventory

Policy


DIS Distribution

Schedule

PCO Sourcing


DSS

COMMON

DATA MODEL

INFORMATION

SYSTEM


Tactical Planning


Demand Planning

INV Inventory

Policy


DIS Distribution

Schedule

PCO Sourcing


DSS

COMMON

DATA MODEL

INFORMATION

SYSTEM

FICO™ MOSEL

SUPPORTS DESIGN, IMPLEMENTATION,

START UP AND MAINTENANCE OF COMPLEX DECISION SUPPORT SYSTEMS,

USING AN UNIFIED DEVELOPMENT ENVIRONMENT

ALGEBRAIC LANGUAGE

ELEMENTS

ALGEBRAIC LANGUAGES

• Algebraic Programming Language

• Database Algebraic Language

USER INTERFACE

• Based in database tables

• Operates in LANs and WANs (“Cloud Computing”)

• Visual Interface (MS-Windows)

• Filling the blanks parameterization

SERVICES

• Data-Model Generator

• Final User Interface Generator

• General Language Model Generator (C, Java …), includes Matrix Generator

• Algebraic Language Model Generator (GAMS, IBM ILOG OPL, MOSEL , AIMMS … )

PROBLEM SOLUTION

• Basic problems: LP, MIP, QP, MIQP, NLP

• Large Scale Theory: Benders Partition, Lagrangean Relaxation, Disjunctive Programming, …

• Links to multiple optimization libraries (GUROBI, IBM CPLEX, XPREXX, COIN-MP, … )

• Automatic Generation of Non-anticipative Multistage Stochastic Programming (MSP)

• Parallel solution in computers grids

CONNECTIVITY

• ERP/WMS/TMS/AMS: Enterprise Information Systems

• GIS: Geographic Information Systems

• ASP: Applications Service Provider (MS-Project, Google MAPS, …)

ELEMENTS

ALGEBRAIC LANGUAGEs: • Programming Language

• Database Language

ALGEBRAIC LANGUAGES OBJECTS

MATHEMATICAL DEFINITIONS

• Index, Sets, Parameters, Variables, Equations, Objective Functions, Planning Horizons, Decision Trees

DECISION SUPPORT SYSTEMS

• Problems = S (Equations, Variables, Objective Functions)

• Model = S (Problems, Data Flows)

• DSS = S (Models, Data Flows)

DATA MODEL

• DSN, Data Tables, Fields, Shell Windows, Data Windows, Menus

OPTEX DATABASE ALGEBRAIC LANGUAGE

OPTEX- DATABASE ALGEBRAIC LANGUAGE

SQL

Server

Internet - Intranet

MM

Server

MATHEMATICAL

MODEL

SERVER

INFORMATION

SYSTEM

EASY DEVELOPMENT MATHEMATICAL MODELS IN A LAN-WAN ENVIRONMENT USING THE POWER

OF THE DATABASE SERVERS


SQL

Server

Internet - Intranet

MM

Server

MATHEMATICAL

MODEL

SERVER

INFORMATION

SYSTEM

THE IMPLEMENTATION OF A DECISION SUPPORT SYSTEMS IS BASED IN

A FILLING THE BLANKS PROCESS


MATHEMATICAL MODELS BASIC ELEMENTS ARE STORED IN A DATA BASE

JVB-08/94OPTEX

Min St Sj Sh CTt(GTjth)

sujeto a:

GDzth = SuTN(z) LDuzth

GDzth + GHAzth + DEFzth = DEMzth

ENuth - SjL1(u) GTEjuth

- SvL2(u) LLvuth = 0

. . . . .

z NOD

t = 1,T

h = 1,NH

z NOD

t = 1,T

h = 1,NH

u LIN

t = 1,T

h = 1,NH

INDEXESINDEXES


JVB-08/94OPTEX


sujeto a:





. . . .

z NOD

t = 1,T

h = 1,NH

z NOD

t = 1,T

h = 1,NH

u LIN

t = 1,T

h = 1,NH

SETSSETS



DATABASE CONNECTIVITY

AUTOMATIC GENERATION OF MATHEMATICAL MODEL- DATA MODEL

SQL CONNECTIVITY

JVB-08/94OPTEX


sujeto a:





. . . .

z NOD

t = 1,T

h = 1,NH

z NOD

t = 1,T

h = 1,NH

u LIN

t = 1,T

h = 1,NH

PARAMETERSPARAMETERS



DATABASE CONNECTIVITY

TIPO DE SERIE INTERPRETACIÓN

E ESCALÓN

(STEP)

I

IMPULSO (PULSE)

P

POLI LÍNEA (POLY LINE)


MULTIPLES FORMS OF DATA INTERPRETATION

JVB-08/94OPTEX


sujeto a:





. . . .

z NOD

t = 1,T

h = 1,NH

z NOD

t = 1,T

h = 1,NH

u LIN

t = 1,T

h = 1,NH

VARIABLES


JVB-08/94OPTEX


sujeto a:





. . . .

z NOD

t = 1,T

h = 1,NH

z NODt = 1,T

h = 1,NH

u LINt = 1,T

h = 1,NH

CONSTRAINTS



COORDINATION DECISIONS OVER SPACE AND TIME

MO

IL

MO

WO MO

Tiempo


FOR DISCRETE TIME MODELS, THE PLANNING HORIZON MAY BE IN YEARS,

MONTHS, DAY, HOURS, MINUTES, …

PROBLEMS

MODELS

OPTEX – DECISION SUPPORT SYSTEM ELEMENTS

A PROBLEM IS A COLLECTION OF CONSTRAINTS

A MODEL IS A COLLECTION OF PROBLEMS

CONNECTED BY A DATA FLOW AND A MODEL CONTROL

IN OPTEX IS DIRECT THE UNION OF MATHEMATICAL PROGRAMMING PROBLEMS TO GENERATE A NEW MODEL OR VARIATION OF AN

ALREADY EXISTING MODEL

= +

A DECISION SUPPORT SYSTEM IS A COLLECTION OF MODELS AND DATA FLOW ALL USING THE SAME DATA MODEL

AND THE SAME FRAMEWORK

PTA Aggregated Industrial

Operations Tactical Plannings

DEM Demand

Long/Medium/Short Term

INV Inventory Policies

Demand Forecasting Medium/Short Term

Demand Stages Medium/Short Term

Inventory Policies

Production Goals

POD Production Scheduling

DIS Distribution scheduling

Distribution Goals

PCO Sourcing

Scheduling

Consumption Goals

Production Orders

Distriution Orders

Purchase Orders


Marjet Stages Long/Medium Term

Expansion Plans

DSS

DSS

MODELS

OPTEX – DECISION SUPPORT SYSTEMS ELEMENTS

ADVANCED OPTIMIZATION

INVESTMENTS COORDINATOR

INTERZONE

COORDINATOR

SECTOR 1

STOCHASTIC 1

INTERZONE

COORDINATOR

SECTOR 1

STOCHASTIC 1

INTERSECTOR OPERATIONS

COORDINATOR

STOCHASTIC CONDITION 1

DYNAMIC

COORD.

ZONA S.1

DYNAMIC

COORD.

ZONA S.ZS

DYNAMIC

COORD.

ZONE 1.1

DYNAMIC

COORD.

ZONA 1.Z1

1 T 2 T-1 1 T 2 T-1 1 T 2 T-1 1 T 2 T-1 TIME

PA

RT

ITIO

N

INVESTMENTS

SECTOR

ZONE

DECOMPOSITION MULTILEVEL

SYSTEM

INTERZONE

COORDINATOR

SECTOR 1

STOCHASTIC H

INTERZONE

COORDINATOR

SECTOR 1

STOCHASTIC H


COORDINATOR

STOCHASTIC CONDITION H

DYNAMIC

COORD.

ZONA S.1

DYNAMIC

COORD.

ZONA S.ZS

DYNAMIC

COORD.

ZONE 1.1

DYNAMIC

COORD.

ZONA 1.Z1

1 T 2 T-1 1 T 2 T-1 1 T 2 T-1 1 T 2 T-1

RANDOM

OPERATIONS

NON-ANTICIPATIVE STOCHASTIC OPTIMIZATION

PROBABILISTICS CONSTRAINTS

BENDERS PARTITIONING THEORY

LAGRANGIAN RELAXATION

PARAMETRIC PROGRAMMING

DISJUNCTIVE PROGRAMMING

AUTOMATIC LINEARIZATION

….

LARGE SCALE OPTIMIZATION AND

DECISION SUPPORT SYSTEM ELEMENTS

MODELS PROBLEMS DSSs


INTEGRATED MODEL

INVESTMENTS

- OPERATIONS

OPTEX- LARGE SCALE METHODOLOGIES

INVESTMENTS

COORDINATOR

INTERZONE

COORDINATOR

SECTOR 1

STOCHASTIC 1

INTERZONE

COORDINATOR

SECTOR 1

STOCHASTIC 1


COORDINATOR

STOCHASTIC CONDITION 1

DYNAMIC

COORD.

ZONA S.1

DYNAMIC

COORD.

ZONA S.ZS

DYNAMIC

COORD.

ZONE 1.1

DYNAMIC

COORD.

ZONA 1.Z1

1 T 2 T-1 1 T 2 T-1 1 T 2 T-1 1 T 2 T-1 TIME

PA

RT

ITIO

N

INVESTMENTS

SECTOR

ZONE

DECOMPOSITION

MULTILEVEL

SYSTEM

INTERZONE

COORDINATOR

SECTOR 1

STOCHASTIC H

INTERZONE

COORDINATOR

SECTOR 1

STOCHASTIC H


COORDINATOR

STOCHASTIC CONDITION H

DYNAMIC

COORD.

ZONA S.1

DYNAMIC

COORD.

ZONA S.ZS

DYNAMIC

COORD.

ZONE 1.1

DYNAMIC

COORD.

ZONA 1.Z1

1 T 2 T-1 1 T 2 T-1 1 T 2 T-1 1 T 2 T-1

RANDOM

OPERATIONS

PROBLEMS <-> MODELS

OPTEX- LARGE SCALE METHODOLOGIES

HYDRAULIC SYSTEM COORDINATOR PROBLEM: MODBENCO

CCP, CGH, CGS, COE, CSP, EQE, SQE

yk

ELECTRIC SYSTEM SUB-PROBLEM: MODBENUNNU

DUN, NUN

pk

vk

OPTEX- BENDERS IMPLEMENTATION

HYDRAULIC SYSTEM COORDINATOR PROBLEM: MODBENCO

CCP, CGH, CGS, COE, CSP, EQE, SQE

yk

ELECTRIC SYSTEM SUB-PROBLEM: MODBENNU

DUN, NUN

pk

vk

MODEL: MODBENNU

OPTEX- BENDERS IMPLEMENTATION

Scenario H

Scenario 1

Scenario 2

ARBOL DE DECISIONES DE MULTIPLES ETAPAS

t = 1 t = 2 t = 3 t = 4

OPTEX- MULTISTAGE STOCHASTIC OPTIMIZATION

OPTEX HAS TOOLS ORIENTED TO DEVELOP MULTISTAGE STOCHASTIC OPTIMIZATION MODELS

AUTOMATIC CONVERSION OF A

DETERMINISTIC MODEL INTO STOCHASTIC

MULTI-STAGE DECISION TREE

OPTEX HAS TOOLS ORIENTED TO DEVELOP MULTISTAGE STOCHASTIC OPTIMIZATION

INCLUDING MULTIPLES TYPES OF RISK CONSTRAINTS

Conditional Value-at-Risk (CVaR)

Cost Probability Function

Standard Deviation

(s)

VaR

b=0.05 1.645 s

Cost - f(x|w) a(b)

f ( f(x|w) )

jb( f(x|w) )

OPTEX- MULTISTAGE STOCHASTIC OPTIMIZATION

AUTOMATIC CONVERSION

OF ANY DETERMINISTIC MODEL INTO A STOCHASTIC MODEL

DETERMINISTIC CASE

t = 1 t = 2

Mean Demand

Deterministics Decisions

Deterministics Future Operations

Decisions

TWO-STAGE DECISION TREE FOR DEMAND: UNCERTAINTY DIMENSION

t = 1 t = 2

Scenario Demand 10

Scenario Demand 1

Scenario Demand 2


0.10

0.10

Uncertainty Future Operations

Decisions

Demand 10

Demand 1

Demand 2

0.10

0.10

Demand 10

Demand 1

Demand 2

0.10

0.10

WITHOUT Extrem Event

0.90

0.10

t = 1 t = 2


Uncertainty Future Operations

Decisions

TWO-STAGE DECISION TREE FOR DEMAND: UNCERTAINTY DIMENSION 1

EXTREME EVENT: UNCERTAINTY DIMENSION 2

WITH Extrem Event

THE AUTOMATIC CONVERSION IMPLIES:

1. TO INCLUDE THE INDEXES RELATED WITH THE UNCERTAINTY DIMENSIONS

1.


2. TO DEFINE A DECISION TREE

3. TO SPECIFY THE NON ANTICIPATIVE VARIABLES

4. TO SPECIFY THE PARAMETERS WITH THE UNCERTAINTY DIMENSIONS

3.

4.

2.


5. TO LINK THE MODEL WITH THE DECISION TREE

5.


6. TO INCLUDE IN THE TABLES THE FIELDS ASSOCIATED TO THE UNCERTAINTY DIMENSIONS

6.

OPTEX PROGRAMMING ALGEBRAIC LANGUAGE

(like GAMS, AMPL, LPL, …)

OPTEX PROGRAMMING ALGEBRAIC LANGUAGE

AUTOMATIC DOCUMENTATION

Internet-Intranet

SERVIDOR MODELOS

MATEMÁTICOS

OPTEX WIDE AREA NETWORK

DOCUMENTATION

OPTEX generates automatically the following documentation:

Algebraic Formulation

Information system data model

Connectivity with other data models

Remote Access Server Connectivity

RTF DOCUMENT

GENERATED BY OPTEX

RTF FIELD

FILLED BY OPTEX

PROBLEM SOLUTION

OPTEX – MATHEMATICAL PROBLEM FORMATS

OPTEX-MMS incorporates optimization methodologies depending on

the optimization library that is being used.

• LINEAR PROGRAMMING (LP)

• MIXED INTEGER PROGRAMMING (MIP).

• MIXED BINARY PROGRAMMING (BP)

• QUADRATIC PROGRAMMING (QP)

• QUADRATIC MIXED PROGRAMMING (QMP)

• QUADRATIC PROGRAMMING (QP-QR)

• INTEGER QUADRATIC PROGRAMMING (QMP-QR)

• NON-LINEAR PROGRAMMING (NLP)

• MIXED COMPLEMENTARITY PROGRAMMING (MCP)

OPTEX PROCESSOR

MODELS GAMS – MPS

IBM ILOG OPL MOSEL – AIMMS - …

MODEL RESULTS (PRIMAL – DUAL)

DATABASE ALGEBRAIC LANGUAGE

OPTEX PROCESSOR

MODELS

C PROGRAMS

LIB or DDL LIBRARY

OPTEX WIDE AREA NETWORK

Internet-Intranet

SERVIDOR MODELOS

MATEMÁTICOS

Remote access server connectivity

CLOUD SERVER

ALGEBRAIC LANGUAGE

SOLVER

C ANSI

SOLVER

CLOUD LINK

SOLVING C MODELS

Internet

MATHEMATICAL MODEL’S ERVER

OPTEX

ERP

DATABASE

Remote Access Server

Connectivity

OPTEX Graphic User Interface

OPTEX Mathematical Modeling

Processor

ODBC

USUARIOS ILIMITADOS

OPTIMIZATION LIBRARY

CPLEX

FICO™ XPRESS

MATHEMATICAL MODEL

C LANGUAGE

OPTEX – C DSS PROGRAM STRUCTURE

I/O Routines

MODELs Routines

Main

OPTEX-COINLP LINK

Routine

COINLP Routines

CPLEX Routines

CONSTRAINTs Routines

OPTEX-CPLEX LINK

Routine

OPTEX-xxxxx LINK

Routine

XXXXX Routines

PROBLEMs Routines

LARGE SCALE OPTIMIZATION Routines

DSS.LIB or DSS.DLL DSS

DATABASE

OPTEX – C DSS PROGRAM STRUCTURE

MODELs Routines

OPTEX-COINLP LINK

Routine

COINLP Routines

CPLEX Routines

CONSTRAINTs Routines

OPTEX-CPLEX LINK

Routine

OPTEX-xxxxx LINK

Routine

XXXXX Routines

PROBLEMs Routines

LARGE SCALE OPTIMIZATION Routines

DSS.LIB or DSS.DLL DSS

DATABASE

USER Routines

OPTEX-USER LINK

Routine

Customized Visual User Interface

USER ERP

USER TRANSACTIONAL SQL DATABASE

MATHEMATHICAL MODEL.EXE

Customized Visual User Interface

OPTEX: PRODUCTION PHASE

SOLVING GAMS MODELS

Internet

OPTEX

ERP

DATABASE



ODBC


Processor

CPLEX

FICO™ Xpress


Internet

OPTEX

ERP

DATABASE


ODBC


Processor

CPLEX



FICO™ Xpress

MATHEMATICAL MODEL

GAMS ALGERAIC LANGUAGE

SOLVING IBM-OPL MODELS

Internet

OPTEX

ERP

DATABASE



Processor

ODBC

CPLEX OPL



MATHEMATICAL MODEL

IBM-OPL LANGUAGE

IBM-ODM FRAMEWORK

SOLVING MOSEL-XPRESS MODELS

Internet

OPTEX

ERP

DATABASE



Processor

ODBC Remote Access Server

Connectivity


MATHEMATICAL MODEL

MOSEL ALGERAIC LANGUAGE

SOLVING AIMMS MODELS

Internet

OPTEX

ERP

DATABASE



Processor


Connectivity


CPLEX

FICO™ Xpress

MATHEMATICAL MODEL

AIMMS ALGERAIC LANGUAGE

SOLVING AMPL MODELS

(UNDER DEVELOPMENT)

Internet

OPTEX

ERP

DATABASE



Processor


Connectivity


UNDER DEVELOPMENT

CPLEX

FICO™ Xpress

MATHEMATICAL MODEL

AIMMS ALGERAIC LANGUAGE MATHEMATICAL MODEL

AMPL ALGERAIC LANGUAGE

SOLVING iAL IMPRESS MODELS

(UNDER DEVELOPMENT)

SUPER STRUCTURE

&sUnit,&sOperation,&sPort,&sState

IMPRESS

SIMM: MATHEMATICAL

MODEL INFORMATION

SYSTEM

SIDI: INDUSTRIAL

DATA INFORMATION

SYSTEM

(UOPSS) IMPRESS Files

POSSIBLE FUTURE LINKS

http://www.python.org/

INFORMATION SYSTEMS CONNECTIVITY

INDUSTRIAL DATA INFORMATION SYSTEM

INFORMATION SYSTEM


sujeto a:

GDzth - SuTN(z) LDuzth = 0




Sistema Descripción Capacidad

Térmica (MW)

EEB.

ISA.

EPM

COR

Energía Eléctrica de Bogotá

Interconexión Eléctrica S.A.

Empresas Públicas de Medellín

CORELCA

45

67

0

78

SIMM: MATHEMATICAL MODEL INFORMATION SYSTEM

SIDI: INDUSTRIAL DATA INFORMATION SYSTEM

IMPLEMENTATION OF THE INDUSTRIAL DATA

INFORMATION SYSTEM

SIMM – SIDI RELATION

INDEX

Parameter

Restricción

Indexes Variable

Indexes

Indexes

ENTITY

ENTITIES RELATIONS

SIMM: MATHEMATICAL

MODEL INFORMATION

SYSTEM

SIDI: INDUSTRIAL

DATA INFORMATION

SYSTEM

Indexes Sets

IMPLEMENTATION INDUSTRIAL DATA INFORMATION SYSTEM

IN OPTEX THE IMPLEMENTATION OF THE INDUSTRIAL DATA INFORMATION SYSTEM IS

BASED IN A FILLING THE BLANKS GUIDED PROCESS, SIMILAR TO THE PROCESS TO

IMPLEMENTATION OF THE MATHEMATICAL MODELS.

THE MODELER DOESN’T NEED TO BE AN SPECIALIST

IN DATABASES LANGUAGES AND INFORMATION SYSTEMS

IN OPTEX THE IMPLEMENTATION OF THE INDUSTRIAL DATA INFORMATION SYSTEM IS

BASED IN A FILLING THE BLANKS GUIDED PROCESS, SIMILAR TO THE PROCESS TO

IMPLEMENTATION OF THE MATHEMATICAL MODELS.

THE MODELER DOESN’T NEED TO BE AN SPECIALIST

IN DATABASES LANGUAGES AND INFORMATION SYSTEMS


TABLES DEFINITION

FIELDS DEFINITION

INDEX TABLES DEFINITION RELATIONAL FIELDS DEFINITION


EXPLORER MENU DEFINITION


RELATIONAL INFORMATION SYSTEM

OPTEX

INFORMATION SYSTEM


IS A COLLECTION OF:

DATA TABLES, SHELL WINDOWS, DATA

WINDOWS AND MENUS ORIENTED TO THE FINAL USER



THE DATABASE OF THE INFORMATION SYSTEM IS A COLLECTION OF RELATIONAL DATA TABLES

ORIENTED TO MANAGE LARGE AMOUNT OF DATA, LIKE IN THE REAL WORLD MODELS.

OPTEX GENERATES, ON-LINE, DATA WINDOWS WITH A COLLECTION OF

WINDOWS-TOOLS THAT HELP THE USER IN THE LABOR OF DATA CAPTURE.

THE DATA WINDOWS ARE JOINT IN A SHELL

WINDOWS IN A RELATIONAL APPROACH.


BREWING PLANTS BREWING PLANT PRODUCT

BREWING PLANT HOURS

BREWING PLANT RESOERCE PRODUCT

BREWING PLANT INITIAL CONDITIONS

BREWING PLANT RESOURCE

BREWING PLANT FACTORY

OPTEX FORM WINDOW TO CAPTURE/MODIFY DATA INCLUDING HELP TOOLS

OPTEX EXPLORER WINDOWS TO MAINTENANCE DATA TABLES

HIERARCHIC INFORMATION SYSTEM FOR MODELS RESULTS

SCENARIO FAMILY ROOT DIRECTORY

Family No. 1

Directory

Family No. E

Directory

Family No. n

Directory

Scenario No. E-X

Directory

Scenario No. E-X

Directory

Tables Sets

Parameters

Tables Sets

Parameters

Tables Variables

Primal-Dual

Tables Sets

Parameters

Tables Variables

Primal-Dual

Scenario No. E-X

Directory

Tables Sets

Parameters

Tables Variables

Primal-Dual

AUTOMATICALLY, OPTEX GENERATES A HIERARCHIC INFORMATION SYSTEM TO STORE THE RESULTS OF THE MODELS USING THE

CONCEPTS OF SCENARIOS AND FAMILY OF SCENARIOS.

OPTEX STORES THE RESULTS

IN DATA TABLES

AND/OR IN TEXT FILES AND/OR IN EXCEL FILES


DATA MODEL

INFORMATION SYSTEM

DATABASE ALGEBRAIC LANGUAGE

MODELS IN PROGRAMS

C - GAMS – OPL – AIMMS

…

RTF

DESIGN IMPLEMENTATION

MANUAL

END USER VISUAL

INTERFACE

MODELERS

USERS

OPTEX PROCESSOR

OPTEX-GUI

1

2

3

4

5a

6

7

5c

MODELERS

5b

ASP - CONNECTIVITTY

DECISION SUPPORT

INFORMATION SYSTEM

OR SCIENTISTS

VISUALIZATION TOOLS

CONNECTIVITY

DECISION SUPPORT

INFORMATION SYSTEM

ERP TMS WMS

EDN USER

INFORMATION SYSTEM

XML MAPING ODBCs

Web Services

DECISIONMAKERS

OR SCIENTISTS

VISUALIZATION TOOLS

CONNECTIVITY

OPEN PROJECT MS-PROJECT

IBM ILOG JViews

GEOGRAPHIC INFORMATION

SYSTEM

OLAP

MDX SERVER

CLIENT – SERVER ARCHITECTURE

OPTEX SQL DATABASE

OPTEX - SERVER MATHEMATICAL

MODELING PROCESSOR

OPTEX CLIENT

OPTEX SQL DATABASE

ERP/TMS/WMS DATABASE

OPTEX OLAP DATABASE

OPTEX - SERVER MATHEMATICAL

MODELING PROCESSOR

OPTEX CLIENT VISUALIZATION

SERVER

CLOUD LINK

EXCEL

PROGRAMS IN DIFERENT LANGUAGES

C – GAMS – IBM OPL –

MOSEL – AIMMS - AMPL

MPS

MODEL

OPTEX

CLOUD SERVER

EXCEL

OUTPUT DATA

EXCEL

INPUT DATA

OPCHAIN OPTIMIZING THE VALUE CHAIN

To capitalize its expertise in mathematical optimization projects, DW created OPCHAIN, a brand through which we have grouped the solutions developed by DW, in different areas of application using mathematical programming methodologies and technologies.

In 2012, OPCHAIN has accumulated the experience of more than thirty-five (35) years in engineering problem solving and business analytics using mathematical programming models. OPCHAIN models are fully programmable, easy to customize for each client, and are easily integrated with other IT solutions in organizations.

OPCHAIN OPTIMIZING THE VALUE CHAIN

OPCHAIN-SCO SUPPLY CHAIN OPTIMIZATION

OPCHAIN-TSO TRANSPORT SYSTEMS OPTIMIZATION

OPCHAIN-RSO RETAIL CHAIN OPTIMIZATION

OPCHAIN-RPO REGIONAL PLANING OPTIMIZATION

OPCHAIN-ESO ENERGY SYSTEMS OPTIMIZATION

OPCHAIN-BANK BANK SYSTEMS OPTIMIZATION

OPCHAIN-EDO EDUCATIONAL SYSTEMS OPTIMIZATION

OPCHAIN-MINES MINES SYSTEMS OPTIMIZATION

OPTEX Mathematical Modeling System, was developed to support

DecisionWare’s mathematical modeling projects since 1991.

OPTEX has supported the development of all multi-model OPCHAIN-DSS

developed by

SERVICES

TO SELL OPTEX MATHEMATICAL MODELING MANAGEMENT SYSTEM

TO SELL OPCHAIN-MODELS IN ANY PLATFORM

(INCLUDING SOURCE CODE)

TO CONVERT MODELS FROM ANY PLATFORM TO ANY PLATFORM

TO DEVELOPMENT ON DEMAND MODELS IN ANY PLATFORM

www.decisionware.net

optex mathematical modeling system

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