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Self-adaptive Orthogonal Simplified Swarm Optimization for the Series-Parallel Redundancy Allocation Problem

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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))

Abstract

This work presents a novel self-adaptive orthogonal simplified swarm optimization scheme (SR-SSO) that combines repetitive orthogonal array testing (ROAT), self-adaptive parameter control, and SSO to the series-parallel redundancy allocation problem (RAP) with a mix of components. The RAP is to decide a network structure to minimize the manufacturing cost under the reliability limitation by using redundant components in parallel. The results obtained in extensive experiments indicate that the proposed algorithm outperforms the previously-developed algorithms in the literature.

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Author information

Authors and Affiliations

  1. Integration and Collaboration Laboratory, Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Taiwan, Hsinchu

    Wei-Chang Yeh

  2. Department of Logistics and Shipping Management, Kainan University, Luzhu Township, Taiwan

    Chia-Ling Huang

Authors
  1. Wei-Chang Yeh
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  2. Chia-Ling Huang
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Corresponding author

Correspondence to Wei-Chang Yeh .

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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Yeh, WC., Huang, CL. (2015). Self-adaptive Orthogonal Simplified Swarm Optimization for the Series-Parallel Redundancy Allocation Problem. 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_16

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  • DOI: https://doi.org/10.1007/978-3-319-13356-0_16

  • 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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