Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (2): 20-28.DOI: 10.3778/j.issn.1002-8331.1710-0292

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Review of hybrids of GA and PSO

LI Hongya1, PENG Yuzhong1,2, DENG Chuyan1, GONG Daoqing1   

  1. 1.Key Laboratory of Scientific Computing & Intelligent Information Processing in Universities of Guangxi, School of Computer & Information Engineering, Guangxi Teacher Education University, Nanning 530022, China
    2.School of Computer Science, Fudan University, Shanghai 200433, China
  • Online:2018-01-15 Published:2018-01-31

GA与PSO的混合研究综述

李红亚1,彭昱忠1,2,邓楚燕1,龚道庆1   

  1. 1.广西师范学院 计算机与信息工程学院 科学计算与智能信息处理广西高校重点实验室,南宁 530022
    2.复旦大学 计算机科学技术学院,上海 200433

Abstract: The traditional algorithms can’t solve the complex problems of large-scale, multivariable and multi-constraint, which lead to more and more extensive application of intelligent algorithm. However, the hybrid algorithm of complementary algorithm is created because the single intelligent algorithm also has some disadvantages. In this paper, it briefly summarizes the?hybrid of classical intelligent algorithm Genetic Algorithm(GA) and Particle Swarm Optimization(PSO). Except that, further research direction about it will be discussed.

Key words: genetic algorithm, particle swarm algorithm, evolutionary algorithm, intelligent computing, intelligent hybrid

摘要: 传统算法无法满足现代大规模、多变量、多约束的复杂问题求解,使得智能算法的应用越来越广泛。但单一智能算法在解决很多复杂问题时依然存在不足,利用算法之间互补性的混合算法便应运而生,并且取得了较好的实验效果,被越来越多的国内外学者所关注。以混合方式为研究主线,对智能算法中的遗传算法(GA)和粒子群算法(PSO)的融合方式进行分析与综述,并对其进一步的研究发展方向进行了探讨。

关键词: 遗传算法, 粒子群算法, 演化算法, 智能计算, 智能混合