Applying software engineering techniques in the development and management of linear and integer programming applications

This work addresses characteristics of software environments for mathematical modeling and proposes a system for developing and managing models of linear and integer programming (IP) problems. The main features of this modeling environment are: version control of models and data; client‐server archi...

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Bibliographic Details
Published in:International transactions in operational research Vol. 21; no. 6; pp. 1001 - 1030
Main Authors: Costa, Fernando, Murta, Leonardo, Ribeiro, Celso C.
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01.11.2014
Subjects:
Integer programming
linear programming
mathematical modeling
Mathematical programming
Operations research
Optimization
Software
Software engineering
Studies
version control
ISSN:0969-6016, 1475-3995
Online Access:Get full text
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Summary:This work addresses characteristics of software environments for mathematical modeling and proposes a system for developing and managing models of linear and integer programming (IP) problems. The main features of this modeling environment are: version control of models and data; client‐server architecture, which allows the interaction among modelers and decision makers; the use of a database to store information about the models and data scenarios; and the use of remote servers of optimization, which allows the optimization problems to be solved on different machines. The modeling environment proposed in this work was validated using mathematical programming models that exploit different characteristics, such as the treatment of conditions for generating variables and constraints, the use of calculated parameters derived from other parameters, and the use of integer and continuous variables in mixed IP models among others. This validation showed that the proposed environment is able to treat models found in various application areas of operations research and to solve problems with tens of thousands of variables and constraints.
Bibliography:ArticleID:ITOR12123
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ObjectType-Feature-1
content type line 14
ISSN:0969-6016
1475-3995
DOI:10.1111/itor.12123