Constraint handling improvements for multiobjective genetic algorithms

被引：101

作者：

Kurpati, A ^{[1
]}

Azarm, S ^{[1
]}

Wu, J ^{[1
]}

机构：

[1] Univ Maryland, Dept Mech Engn, College Pk, MD 20742 USA

来源：

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION | 2002年 / 23卷 / 03期

关键词：

genetic algorithms; multiple objectives; constraint handling;

D O I：

10.1007/s00158-002-0178-2

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Four constraint handling improvements for Multi-Objective Genetic Algorithms (MOGA) are proposed. These improvements are made in the fitness assignment stage of a MOGA and are all based upon a "Constraint-First-Objective-Next" model. Two multi-objective design optimization examples, i.e. a speed reducer design and the design of a fleet of ships, are used to demonstrate the improvements. For both examples, it is shown that the proposed constraint handling techniques significantly improve the performance of a baseline MOGA.

引用

页码：204 / 213

页数：10

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