Genetic algorithm for non-linear mixed integer programming problems and its applications

In this paper we propose a method for solving non-linear mixed integer programming (NMIP) problems using genetic algorithm (GAs) to get an optimal or near optimal solution. The penalty function method was used to evaluate those infeasible chromosomes generated from genetic reproduction. Also, we app...

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Bibliographic Details
Published in:Computers & industrial engineering Vol. 30; no. 4; pp. 905 - 917
Main Authors: Yokota, Takao, Gen, Mitsuo, Li, Yin-Xiu
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 01.09.1996
Pergamon Press Inc
Subjects:
Algorithms
Applications
Genetic algorithms
Industrial engineering
Integer programming
Nonlinear programming
Studies
ISSN:0360-8352, 1879-0550
Online Access:Get full text
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Summary:In this paper we propose a method for solving non-linear mixed integer programming (NMIP) problems using genetic algorithm (GAs) to get an optimal or near optimal solution. The penalty function method was used to evaluate those infeasible chromosomes generated from genetic reproduction. Also, we apply the method for solving several optimization problems of system reliability which belong to non-linear integer programming (NIP) or (NMIP) problems, using the proposed method. Numerical experiments and comparisons with previous works are illustrated to demonstrate the efficiency of the proposed method.
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ISSN:0360-8352
1879-0550
DOI:10.1016/0360-8352(96)00041-1