A GA and Particle Swarm Optimization Based Hybrid Algorithm

被引：23
|
作者：
Nie Ru
Yue Jianhua
机构：
来源：
2008 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-8 | 2008年
关键词：
D O I：
10.1109/CEC.2008.4630925
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper an improved particle swarm algorithm is presented firstly and then a hybrid method combining Genetic Algorithm(GA) and Particle Swarm Optimization(PSO) is proposed. This hybrid technique incorporates concepts from GA and PSO and creates individuals in a new generation not only by crossover and mutation operations as found in GA but also by mechanisms of PSO. It can solve the problem of local minimum of the particle swarm optimization and has higher efficiency of search. Simulation results show that the proposed method is effective for the optimization problems.
引用
收藏
页码：1047 / 1050
页数：4
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