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The Extraordinary Particle Swarm Optimization and Its Application in Constrained Engineering Problems

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Harmony Search Algorithm (ICHSA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 514))

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Abstract

The particle swarm optimization (PSO) is a natural-inspire optimization algorithm mimicking the movement behavior of animal flocks for food searching. Although the algorithm presents some advantages and widely application, however, there are several drawbacks such as trapping in local optima and immature convergence rate. To overcome these disadvantages, many improved versions of PSO have been proposed. One of the latest variants is the extraordinary particle swarm optimization (EPSO). The particles in the EPSO are assigned to move toward their own determined target through the search space. The applicability of EPSO is verified by several experiments in engineering optimization problems. The application results show the outperformance of the EPSO than the other PSO variants in terms of solution searching and as well as convergence rate.

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Acknowledgments

This research was supported by a grant (13AWMP-B066744-01) from the Advanced Water Management Research Program funded by the Ministry of Land, Infrastructure, and Transport of the Korean government.

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Authors and Affiliations

  1. Department of Civil, Environmental and Architectural Engineering, Korea University, Seoul, 136-713, South Korea

    Thi Thuy Ngo, Ali Sadollah, Yeon Moon Choo, Sang Hoon Jun & Joong Hoon Kim

  2. K-water Research Institute, Korea Water Resources Corporation, 200 Sintangin-Ro, Daedeok-Gu, Daejeon, 34350, South Korea

    Do Guen Yoo

Authors
  1. Thi Thuy Ngo
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  2. Ali Sadollah
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  3. Do Guen Yoo
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  4. Yeon Moon Choo
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  5. Sang Hoon Jun
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  6. Joong Hoon Kim
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Corresponding author

Correspondence to Joong Hoon Kim .

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Editors and Affiliations

  1. TECNALIA, University of the Basque Country ‎(UPV/EHU), Basque Center for Applied Mathematics (BCAM‎), Bilbao, Spain

    Javier Del Ser

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© 2017 Springer Nature Singapore Pte Ltd.

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Ngo, T.T., Sadollah, A., Yoo, D.G., Choo, Y.M., Jun, S.H., Kim, J.H. (2017). The Extraordinary Particle Swarm Optimization and Its Application in Constrained Engineering Problems. In: Del Ser, J. (eds) Harmony Search Algorithm. ICHSA 2017. Advances in Intelligent Systems and Computing, vol 514. Springer, Singapore. https://doi.org/10.1007/978-981-10-3728-3_5

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  • DOI: https://doi.org/10.1007/978-981-10-3728-3_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3727-6

  • Online ISBN: 978-981-10-3728-3

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