GA-based method for solving constrained optimization problems

被引：0

作者：

机构：

[1] Lin, Dan

[2] Li, Min-Qiang

[3] Kou, Ji-Song

来源：

Lin, D. (ling@public.tpt.tj.cn) | 2001年 / Chinese Academy of Sciences卷 / 12期

关键词：

Calculations - Constraint theory - Functions - Genetic algorithms;

D O I：

暂无

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学科分类号：

摘要：

In trying to solve constrained optimization problems using genetic algorithms, the method to handle the constraints is the key factor to success. Some features of GA (genetic algorithms) and a large class of constrained optimization problems are taken into account and a new method called Fixed Proportion and Direct Comparison (FPDC) is proposed, which combines direct comparison method and the strategy to keep a fixed proportion of infeasible individuals. It is successfully integrated with the ordinary GA. Numerical results show that it is a general, effective and robust method.

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