A hybrid genetic algorithm for constrained optimization problems in mechanical engineering

被引：71

作者：

Bernardino, H. S. ^{[1
]}

Barbosa, H. J. C. ^{[2
]}

Lemonge, A. C. C. ^{[1
]}

机构：

[1] Univ Fed Juiz de Fora, Campus Univ, BR-36036330 Juiz de Fora, MG, Brazil

[2] LNCC, MCT, BR-25651075 Petropolis, RJ, Brazil

来源：

2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS | 2007年

关键词：

D O I：

10.1109/CEC.2007.4424532

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A genetic algorithm (GA) is hybridized with an artificial immune system (AIS) as an alternative to tackle constrained optimization problems in engineering. The AIS is inspired in the clonal selection principle and is embedded into a standard GA search engine in order to help move the population into the feasible region. The procedure is applied to mechanical engineering problems available in the literature and compared to other alternative techniques.

引用

页码：646 / +

页数：3

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