Genetic algorithm for constrained global optimization in continuous variables

被引：35

作者：

Bunnag, D ^{[1
]}

Sun, M

机构：

[1] Chiang Mai Univ, Fac Sci, Dept Math, Chiang Mai 50200, Thailand

[2] Univ Alabama, Dept Math, Tuscaloosa, AL 35487 USA

来源：

APPLIED MATHEMATICS AND COMPUTATION | 2005年 / 171卷 / 01期

关键词：

genetic algorithm; constrained optimization; convergence in probability;

D O I：

10.1016/j.amc.2005.01.075

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

We present a stochastic global optimization algorithm, referred to as a Genetic Algorithin (GA), for solving constrained optimization problems over a compact search domain. It is a real-coded GA that converges in probability to the optimal solution. The constraints are treated through a repair operator. A specific repair operator is included for linear inequality constraints. (c) 2005 Elsevier Inc. All rights reserved.

引用

页码：604 / 636

页数：33

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