摘要
提出一种解决早熟收敛问题的改进遗传算法.通过最小生成树聚类将种群划分为若干个子种群,子种群内的个体之间及不同子种群间的个体之间同时进行遗传操作.同子种群间个体的遗传操作可以保证算法的进化方向和收敛速度,不同子种群间个体的遗传操作可以避免近亲繁殖,提供多样性.分别采用二进制和实数编码,在经典的23个基准函数上的对比测试结果表明,所提出算法具有较好的收敛速度和寻优能力.
An improved genetic algorithm is proposed for solving premature convergence. Firstly, the population is divided into several sub-populations by the minimum spanning tree clustering. Then, the genetic operation is performed among individuals within sub-population which ensures the evolution direction and speed, and that among individuals between different sub-populations which provides diversity by avoiding inbreeding. The experimental results on 23 benchmark functions using binary and real-valued representations show that the proposed algorithm has better convergence and faster speed to get the optimal solution.
出处
《控制与决策》
EI
CSCD
北大核心
2016年第10期1837-1844,共8页
Control and Decision
基金
国家自然科学基金重大研究计划培育项目(91546111)
北京市教委项目(PXM2015 014204 500221)
关键词
遗传算法
早熟收敛
最小生成树聚类
多样性
genetic algorithm
premature convergence
minimum spanning tree clustering
diversity
