Unified particle swarm delivers high efficiency to particle swarm optimization

被引:36
作者
Tsai, Hsing-Chih [1 ,2 ]
机构
[1] Natl Taiwan Univ Sci & Technol, Dept Civil & Construct Engn, Taipei, Taiwan
[2] Natl Taiwan Univ Sci & Technol, Ecol & Hazard Mitigat Engn Researching Ctr, 43,Sec 4,Keelung Rd, Taipei, Taiwan
关键词
Particle swarm optimization; Unified particle swarm; Parameter selection; ARTIFICIAL BEE COLONY; ALGORITHM; MIGRATION;
D O I
10.1016/j.asoc.2017.02.008
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper suggests integrating a unification factor into particle swarm optimization (PSO) to balance the effects of cognitive and social terms. The resultant unified particle swarm (UPS) moves particles toward the center of its personal best and the global best. This improves on PSO, which moves particles far beyond the center. Widely used benchmark functions and four types of experiments demonstrate that the proposed UPS uses slightly more computational time than PSO to attain significantly higher efficiency and, usually, better solution effectiveness and consistency than PSO. Robust performance was further demonstrated by the significantly higher efficiency and better solution effectiveness and stability achieved by the UPS, as compared to the PSO and its variants. Outstandingly, convergence speeds for the proposed UPS were very good on the 13 benchmark functions examined in experiment 1, demonstrating the correct movement of UPS particles toward convergence. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:371 / 383
页数:13
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