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Numerical Simulations for Hybrid Electromagnetism-Like Mechanism Optimization Algorithms with Descent Methods

  • Conference paper
Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems - Volume 2

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 2))

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Abstract

Electromagnetism-like Mechanism (EM) method is known as one of metaheuristics. The basic idea is that the position of a charged particle represents a solution for the optimization problem, and the charge amount of the particle corresponds to the evaluation value of the solution. Starting with a population of particles whose positions are randomly initialized, the population converges to a neighborhood of the optimal or semi-optimal solution. Like other metaheuristics, one of its drawbacks is that it takes too much time to converge to a solution. In this paper, we will perform numerical simulations to investigate how to use and combine EM and steepest descent methods. Further, we will show that hybrid EM methods are superior in accuracy to conventional methods.

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Authors and Affiliations

  1. Graduate School of Science and Engineering, Kagoshima University, 1-21-40, Korimoto, Kagoshima, Japan

    Hirofumi Miyajima

  2. Kagoshima University, 1-21-40 Korimoto, Kagoshima, Japan

    Noritaka Shigei, Hiroki Taketatu & Hiromi Miyajima

Authors
  1. Hirofumi Miyajima
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  2. Noritaka Shigei
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  3. Hiroki Taketatu
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  4. Hiromi Miyajima
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Corresponding author

Correspondence to Hirofumi Miyajima .

Editor information

Editors and Affiliations

  1. Faculty of Science and Technology Department of Infomatics, Kindai University, Higashi-Osaka, Japan

    Hisashi Handa

  2. Department of Computer Science and Intelligent Systems, Osaka Prefecture University, Osaka, Japan

    Hisao Ishibuchi

  3. School of Computer Engineering, Nanyang Technological University, Singapore, Singapore

    Yew-Soon Ong

  4. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore

    Kay-Chen Tan

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© 2015 Springer International Publishing Switzerland

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Miyajima, H., Shigei, N., Taketatu, H., Miyajima, H. (2015). Numerical Simulations for Hybrid Electromagnetism-Like Mechanism Optimization Algorithms with Descent Methods. In: Handa, H., Ishibuchi, H., Ong, YS., Tan, KC. (eds) Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems - Volume 2. Proceedings in Adaptation, Learning and Optimization, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-13356-0_24

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  • DOI: https://doi.org/10.1007/978-3-319-13356-0_24

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13355-3

  • Online ISBN: 978-3-319-13356-0

  • eBook Packages: EngineeringEngineering (R0)

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