摘要
适应值共享遗传算法需要事先给出解空间中峰的数目或峰的半径 ,这对于某些问题来说是有困难的 .针对这类问题 ,提出将峰的半径作为决策变量 ,对其进行编码并放入染色体中参与演化过程 ,利用遗传算法的优化能力在对问题进行优化的同时对个体的峰半径进行自适应调整 .用所提出的方法对多个标准测试问题的优化结果表明 。
It is necessary to provide the number of peaks or the radii of peaks in optimizing a multi modal problem for the existing fitness sharing genetic algorithms. However, these parameters are not available for some real world multi modal problems. A new method is proposed in this paper, which takes the radii of peaks as a part of optimization variables. The radii of peaks are coded, put in the chromosomes and optimized with the variables of the problem by fitness sharing genetic algorithm without a prior knowledge of the above parameters. The empirical results tested by several benchmark problems show that the self adaptive control method for the radii of peaks is very efficient in finding peaks of the problem.
出处
《自动化学报》
EI
CSCD
北大核心
2002年第5期816-820,共5页
Acta Automatica Sinica
基金
清华大学基础研究基金 (JC2 0 0 1 0 1 9)资助
关键词
多峰函数优化
适应值共享
自适应参数调整
遗传算法
Multimodal optimization, fitness sharing, self adaptive parameter control, genetic algorithms
