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A Newly Cooperative PSO – Multiple Particle Swarm Optimizers with Diversive Curiosity, MPSOα/DC

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Intelligent Control and Computer Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 70))

Abstract

In this paper we propose a newly multiple particle swarm optimizers with diversive curiosity (MPSOα/DC) for enhancing the search performance. It has three outstanding features: (1) Implementing plural particle swarms in parallel to explore; (2) Finding the most suitable solution in a small limited space by a localized random search for correcting the solution found by each particle swarm; (3) Introducing diversive curiosity into the multi-swarm to alleviate stagnation. To demonstrate the proposal’s effectiveness, computer experiments on a suite of benchmark problems are carried out. We investigate its intrinsic characteristics, and compare the search performance with other methods. The obtained results show that the search performance of the MPSOα/DC is superior to that by the PSO/DC, EPSO, OPSO, and RGA/E for the given benchmark problems.

This paper was originally presented at IMECS 2010 [26]. This is a substantially extended version.

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Acknowledgements

This research was partially supported by Grant-in-Aid Scientific Research(C) (22500132) from the Ministry of Education, Culture, Sports, Science and Technology, Japan.

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Authors and Affiliations

  1. Department of Brain Science and Engineering, Graduate School of Life Science & Systems Engineering, Kyushu Institute of Technology, 2-4 Hibikino, Wakamatsu, Kitakyushu, 808-0196, Japan

    Hong Zhang

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  1. Hong Zhang
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Correspondence to Hong Zhang .

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Editors and Affiliations

  1. International Association of Engineers, Hung To Road 37-39, Hong Kong, 3739, China, People's Republic

    Sio-Iong Ao

  2. Computer Science, Tijuana Institute of Technology, Tijuana, 91909, Mexico

    Oscar Castillo

  3. Fac. Information Science & Engineering, University of Canberra, Canberra, 2601, Aust Capital Terr, Australia

    Xu Huang

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Zhang, H. (2011). A Newly Cooperative PSO – Multiple Particle Swarm Optimizers with Diversive Curiosity, MPSOα/DC. In: Ao, SI., Castillo, O., Huang, X. (eds) Intelligent Control and Computer Engineering. Lecture Notes in Electrical Engineering, vol 70. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0286-8_7

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  • DOI: https://doi.org/10.1007/978-94-007-0286-8_7

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-0285-1

  • Online ISBN: 978-94-007-0286-8

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