控制理论与应用2004，Vol.21Issue(6)：885-889,5.
随机优化问题基于假设检验的遗传算法
Hypothesis-test based genetic algorithm for stochastic optimization problems
摘要
Abstract
To effectively solve the stochastic optimization problems with non-deterministic and multi-modal properties, a class of hypothesis-test based genetic algorithm is proposed. The algorithm performs reasonable estimation by multiple evaluations, searches the design space effectively via genetic operators, and enhances the searching ability and population diversity by hypothesis test to overcome premature convergence. Based on typical stochastic functional and combinatorial optimization problems, the effects of hypothesis test, performance estimation number and magnitude of noise on the performance of the approach are studied, and the effectiveness and robustness of the proposed approach are demonstrated.关键词
遗传算法/随机优化/假设检验Key words
genetic algorithm(GA)/stochastic optimization/hypothesis test分类
信息技术与安全科学引用本文复制引用
张亮,王凌,郑大钟..随机优化问题基于假设检验的遗传算法[J].控制理论与应用,2004,21(6):885-889,5.基金项目
Supported by the National Natual Science Foundation of China (60204008,60374060) （60204008,60374060）
973 Program(2002CB312200). （2002CB312200）
