Parallel Cat Swarm Optimization

被引：104

作者：

Tsai, Pei-Wei ^{[1
]}

Pan, Jeng-Shyang ^{[1
]}

Chen, Shyi-Ming ^{[2
,3
]}

Liao, Bin-Yih ^{[1
]}

Hao, Szu-Ping ^{[4
]}

机构：

[1] Natl Kaohsiung Univ Appl Sci, Dept Elect Engn, Kaohsiung 807, Taiwan

[2] Natl Taiwan Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taipei, Taiwan

[3] Jinwen Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taipei, Taiwan

[4] Natl Kaohsiung Univ Appl Sci, Dept Mech Engn, Kaohsiung, Taiwan

来源：

PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2008年

关键词：

evolutionary; swarm intelligent; computational intelligence; optimization; parallel swarm;

D O I：

10.1109/ICMLC.2008.4620980

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

We investigate a parallel structure of Cat Swarm Optimization (CSO) in this paper, and we call it Parallel Cat Swarm Optimization (PCSO). In the experiments, we compare Particle Swarm Optimization (PSO) with CSO and PCSO. The experimental results indicate that both CSO and PCSO perform well. Moreover, PCSO is an effective scheme to improve the convergent speed of Cat Swarm Optimization in case the population size is small and the whole iteration is less.

引用

页码：3328 / +

页数：2

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