摘要
针对导致遗传算法早熟收敛的原因,提出一种基于模糊聚类的改进遗传算法(FM-GA),给出了FMGA算法实施的详细步骤,并研究确定了算法控制参数的取值。最后,对FMGA进行了数值仿真,仿真结果表明,FMGA能有效避免早熟收敛,在较短时间内逼近全局最优解,运算结果较基本遗传算法的提高4个数量级,而且运算过程不存在震荡现象。
To solve premature convergence of Genetic Algorithm, Modified Genetic Algorithm based on Fuzzy System （FMGA） is presented, detailed steps for FMGA is developed, and the parameters of FMGA is determined.FM-GA is applied to optimize Camel Function. The simulation results show that FMGA can well prevent premature con-vergence to get global optimal, and this algorithm is accurate and has good stability.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2008年第2期166-169,共4页
Journal of Chongqing University
基金
中国建设部荷兰赠款项目(MOC-NGGP-2003-3)
关键词
遗传算法
模糊聚类
早熟收敛
genetic algorithm
fuzzy system
premature convergence
