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Adaptive Hybrid Genetic Algorithm with Modified Cuckoo Search for Reliability Optimization Problem

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Book cover Proceedings of the Tenth International Conference on Management Science and Engineering Management

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 502))

Abstract

In this paper, an adaptive hybrid genetic algorithm with modified cuckoo search (MCS-AHGA) is proposed for effectively solving reliability optimization problems. For the proposed MCS-AHGA, a modified cuckoo search (MCS) which improves a weakness of conventional cuckoo search (CS) is adapted, and the genetic algorithm with an adaptive search scheme (AGA) is used. Hybridizing the MCS and the AGA can reinforce search quality and speed toward global optimal solution rather than hybridizing conventional CS and GA does. In numerical experiment, three types of reliability optimization problems are used for comparing the performance of the proposed MCS-AHGA with those of various conventional competing approaches including CS and GA. The experimental result proves that the proposed MCS-AHGA outperforms the competing conventional algorithms.

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Acknowledgments

This work is partly supported by JSPS: Grant-in-Aid for Scientific Research (C; No. 15K00357) and by the National Research Foundation of Korea Grant funded by the Korean Government (NRF- 2014S1A5A2A01010951). This paper is a revised and extended version of the paper which was presented in 45th International Conference on Computers and Industrial Engineering, Metz, France, 2015.

Author information

Authors and Affiliations

  1. Division of Business Administration, Chosun University, Gwangju, Korea

    Youngsu Yun

  2. Division of Computer Engineering, Dongseo University, Busan, Korea

    Jungbok Jo

  3. Fuzzy Logic Systems Institute, Tokyo University of Science, Katsushika, Japan

    Mitsuo Gen

Authors
  1. Youngsu Yun
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  2. Jungbok Jo
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  3. Mitsuo Gen
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Corresponding author

Correspondence to Youngsu Yun .

Editor information

Editors and Affiliations

  1. Business School, Sichuan University, Chengdu, Sichuan, China

    Jiuping Xu

  2. Azerbaijan National Academy of Sciences, Baku, Azerbaijan

    Asaf Hajiyev

  3. Karlsruhe Institute of Technology, Karlsruhe, Baden-Württemberg, Germany

    Stefan Nickel

  4. Tokyo University of Science, Fuzzy Logic Systems Institute, Tokyo, Japan

    Mitsuo Gen

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© 2017 Springer Science+Business Media Singapore

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Yun, Y., Jo, J., Gen, M. (2017). Adaptive Hybrid Genetic Algorithm with Modified Cuckoo Search for Reliability Optimization Problem. In: Xu, J., Hajiyev, A., Nickel, S., Gen, M. (eds) Proceedings of the Tenth International Conference on Management Science and Engineering Management. Advances in Intelligent Systems and Computing, vol 502. Springer, Singapore. https://doi.org/10.1007/978-981-10-1837-4_31

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  • DOI: https://doi.org/10.1007/978-981-10-1837-4_31

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-1836-7

  • Online ISBN: 978-981-10-1837-4

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