Constraint handling in genetic algorithms using a gradient-based repair method

被引：165

作者：

Chootinan, P ^{[1
]}

Chen, A ^{[1
]}

机构：

[1] Utah State Univ, Dept Civil & Environm Engn, Logan, UT 84322 USA

来源：

COMPUTERS & OPERATIONS RESEARCH | 2006年 / 33卷 / 08期

基金：

美国国家科学基金会;

关键词：

constraint handling; constrained optimization; genetic algorithms; hybrid method;

D O I：

10.1016/j.cor.2005.02.002

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Constraint handling is one of the major concerns when applying genetic algorithms (GAs) to solve constrained optimization problems. This paper proposes to use the gradient information derived from the constraint set to systematically repair infeasible solutions. The proposed repair procedure is embedded into a simple GA as a special operator. Experiments using 11 benchmark problems are presented and compared with the best known solutions reported in the literature. Our results are competitive, if not better, compared to the results reported using the homomorphous mapping method, the stochastic ranking method, and the self-adaptive fitness formulation method. (c) 2005 Elsevier Ltd. All rights reserved.

引用

页码：2263 / 2281

页数：19

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