Abstract 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.


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    Title :

    Comprehensive Analysis of Cooperative Particle Swarm Optimization with Adaptive Mixed Swarm


    Contributors:
    Jie, Jing (author) / Hou, Beiping (author) / Zheng, Hui (author) / Wu, Xiaoli (author)


    Publication date :

    2014-01-01


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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