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Vector Evolved Multiobjective Particle Swarm Optimization Algorithm

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Abstract

A cooperative multiobjective particle swarm algorithm called vector evolved multiobjective particle swarm optimization (VEMOPSO) algorithm is proposed in this chapter. The algorithm consists of multiple subswarms which connect each other with the ring topology. Each subswarm is designed to optimize one of the objectives, but the update of its particles is performed based on species seeds from neighbor subswarms. When compared with some multiobjective optimization algorithms, the simulation results indicate that the proposed algorithm has a much better performance.

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Acknowledgments

This research was supported by the Specialized Research Fund for the Doctoral Program of Higher Education under grant No. 20100095120016, and the National Natural Science Funds of China under grant No. 61005089.

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Authors and Affiliations

  1. School of Information and Electronic Engineering, China University of Mining and Technology, 221008, Xunzhou, China

    Yong Zhang, Dun-Wei Gong & Cheng-Liang Qi

Authors
  1. Yong Zhang
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  2. Dun-Wei Gong
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  3. Cheng-Liang Qi
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Corresponding author

Correspondence to Yong Zhang .

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Editors and Affiliations

  1. Test, Chongqing University of Technology, The Key Laboratory of Manufacture and, Shapingba Three Gorges square Lihai building 14-C1, Chongqing, 400030, China, People's Republic

    Ran Chen

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Zhang, Y., Gong, DW., Qi, CL. (2012). Vector Evolved Multiobjective Particle Swarm Optimization Algorithm. In: Chen, R. (eds) 2011 International Conference in Electrics, Communication and Automatic Control Proceedings. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8849-2_38

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  • DOI: https://doi.org/10.1007/978-1-4419-8849-2_38

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-8848-5

  • Online ISBN: 978-1-4419-8849-2

  • eBook Packages: EngineeringEngineering (R0)

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