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Multiobjective Particle Swarm Optimization with Directional Search for Distributed Permutation Flow Shop Scheduling Problem

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Bio-inspired Computing: Theories and Applications (BIC-TA 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1159))

Abstract

The distributed permutation flow shop scheduling problem (DPFSP) is a variant of the permutation flow shop scheduling problem (PFSP). DPFSP is closer to the actual situation of industrial production and has important research significance. In this paper, a multiobjective particle swarm optimization with directional search (MoPSO-DS) is proposed to solve DPFSP. Directional search strategy are inspired by decomposition. Firstly, MoPSO-DS divides the particle swarm into three subgroups, and three subgroups are biased in different regions of the Pareto front. Then, particles are updated in the direction of the partiality. Finally, combine the particles of the three subgroups to find the best solution. MoPSO-DS updates particles in different directions which speed up the convergence of the particles while ensuring good distribution performance. In this paper, MoPSO-DS is compared with the NAGA-II, SPEA2, MoPSO, MOEA/D, and MOHEA algorithms. Experimental results show that the performance of MoPSO-DS is better.

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Acknowledgements

This research work is supported by the Sub-Project of National Key R&D Program of China (2017YFD0401001-02), Science & Technology Research Project of Henan Province (162102210044), Program for Science & Technology Innovation Talents in Universities of Henan Province (19HASTIT027), Key Research Project in Universities of Henan Province (17A520030), Ministry of Education and the Grant-in-Aid for Scientific Research (C) of Japan Society of Promotion of Science (JSPS) (19K12148).

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Authors and Affiliations

  1. Henan University of Technology, Zhengzhou, China

    Wenqiang Zhang, Wenlin Hou, Diji Yang & Zheng Xing

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

    Mitsuo Gen

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  1. Wenqiang Zhang
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  2. Wenlin Hou
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  3. Diji Yang
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  4. Zheng Xing
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  5. Mitsuo Gen
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Correspondence to Wenqiang Zhang .

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Editors and Affiliations

  1. Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  2. Zhengzhou University, Zhengzhou, China

    Jing Liang

  3. Zhongyuan University of Technology, Zhengzhou, China

    Boyang Qu

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Zhang, W., Hou, W., Yang, D., Xing, Z., Gen, M. (2020). Multiobjective Particle Swarm Optimization with Directional Search for Distributed Permutation Flow Shop Scheduling Problem. In: Pan, L., Liang, J., Qu, B. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2019. Communications in Computer and Information Science, vol 1159. Springer, Singapore. https://doi.org/10.1007/978-981-15-3425-6_14

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  • DOI: https://doi.org/10.1007/978-981-15-3425-6_14

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3424-9

  • Online ISBN: 978-981-15-3425-6

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