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A hybrid discrete particle swarm optimization for dual-resource constrained job shop scheduling with resource flexibility

Author

Listed:
  • Jing Zhang

    (Zhejiang Police College)

  • Wanliang Wang

    (Zhejiang University of Technology)

  • Xinli Xu

    (Zhejiang University of Technology)

Abstract

In this paper, a novel hybrid discrete particle swarm optimization algorithm is proposed to solve the dual-resource constrained job shop scheduling problem with resource flexibility. Particles are represented based on a three-dimension chromosome coding scheme of operation sequence and resources allocation. Firstly, a mixed population initialization method is used for the particles. Then a discrete particle swarm optimization is designed as the global search process by taking the dual-resources feature into account. Moreover, an improved simulated annealing with variable neighborhoods structure is introduced to improve the local searching ability for the proposed algorithm. Finally, experimental results are given to show the effectiveness of the proposed algorithm.

Suggested Citation

  • Jing Zhang & Wanliang Wang & Xinli Xu, 2017. "A hybrid discrete particle swarm optimization for dual-resource constrained job shop scheduling with resource flexibility," Journal of Intelligent Manufacturing, Springer, vol. 28(8), pages 1961-1972, December.
    • Handle: RePEc:spr:joinma:v:28:y:2017:i:8:d:10.1007_s10845-015-1082-0
    DOI: 10.1007/s10845-015-1082-0
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    References listed on IDEAS

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    1. Xu, J. & Xu, X. & Xie, S.Q., 2011. "Recent developments in Dual Resource Constrained (DRC) system research," European Journal of Operational Research, Elsevier, vol. 215(2), pages 309-318, December.
    2. Moslehi, Ghasem & Mahnam, Mehdi, 2011. "A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search," International Journal of Production Economics, Elsevier, vol. 129(1), pages 14-22, January.
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    Cited by:

    1. Yuanfei Wei & Zalinda Othman & Kauthar Mohd Daud & Shihong Yin & Qifang Luo & Yongquan Zhou, 2022. "Equilibrium Optimizer and Slime Mould Algorithm with Variable Neighborhood Search for Job Shop Scheduling Problem," Mathematics, MDPI, vol. 10(21), pages 1-20, November.
    2. Xiuli Wu & Junjian Peng & Xiao Xiao & Shaomin Wu, 2021. "An effective approach for the dual-resource flexible job shop scheduling problem considering loading and unloading," Journal of Intelligent Manufacturing, Springer, vol. 32(3), pages 707-728, March.
    3. Federica Costa & Matthias Thürer & Alberto Portioli-Staudacher, 2023. "Heterogeneous worker multi-functionality and efficiency in dual resource constrained manufacturing lines: an assessment by simulation," Operations Management Research, Springer, vol. 16(3), pages 1476-1489, September.
    4. Geurtsen, M. & Didden, Jeroen B.H.C. & Adan, J. & Atan, Z. & Adan, I., 2023. "Production, maintenance and resource scheduling: A review," European Journal of Operational Research, Elsevier, vol. 305(2), pages 501-529.
    5. Jose L. Andrade-Pineda & David Canca & Pedro L. Gonzalez-R & M. Calle, 2020. "Scheduling a dual-resource flexible job shop with makespan and due date-related criteria," Annals of Operations Research, Springer, vol. 291(1), pages 5-35, August.

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