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Published in:
2014 | OriginalPaper | Chapter
Comprehensive Analysis of Cooperative Particle Swarm Optimization with Adaptive Mixed Swarm
Authors : Jing Jie, Beiping Hou, Hui Zheng, Xiaoli Wu
Published in: Computational Intelligence, Networked Systems and Their Applications
Publisher: Springer Berlin Heidelberg
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Inspired by the collective intelligence of natural mixed flocking, the paper develops a mixed swarm cooperative search model for particle swarm optimization(MCPSO). Firstly, makes some analysis about the hinting principles and search mechanism behind the natural mixed flocking, and proposes the construction of mixed swarm for optimization. Secondly, introduces the mixed swarm into PSO and researches the main search behaviors of MCPSO, including coarse search and fine search, cooperative search and learning. Finally, the proposed MCPSO was applied to some well-known benchmarks. The experimental results and relative analysis show mixed swarm cooperative search mechanism can greatly benefit the global optimization performance of PSO.