摘要
针对多目标遗传算法的特点 ,基于模糊集理论 ,提出一种基于模糊规则优化的改进模糊遗传算法及其算法结构 ,即用模糊控制的方法来调整遗传算法中的交叉概率和变异概率 ,同时寻找与控制对象相匹配的最佳模糊规则 .在数学函数上的仿真结果表明 ,此种模糊遗传算法不仅加快了解的收敛速度 ,而且大大提高了解的质量 .
Aimed at the characteristics of multi-objective genetic algorithms, an d based on the fuzzy set theory, an improved Fuzzy Genetic Algorithms (FGA) and its algorithm structure was proposed. Fuzzy control method was used to adjust t he genetic algorithms crossover probabilities and mutation probabilities, while searching for the best fuzzy rules correspond to the control objects. The result s of simulation on mathematical functions show that this kind of FGA can improve both the convergent speed and the quality of the solution.
出处
《小型微型计算机系统》
CSCD
北大核心
2005年第1期46-49,共4页
Journal of Chinese Computer Systems
基金
国家"八六三"项目 (2 0 0 2 AA5 170 2 0 )资助
关键词
遗传算法
模糊控制
交叉概率
变异概率
genetic algorithm
fuzzy control
crossover prob ability
mutation probability
