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A multi-objective particle swarm optimisation for integrated configuration design and scheduling in reconfigurable manufacturing system

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  • Jianping Dou
  • Jun Li
  • Dan Xia
  • Xia Zhao

Abstract

To provide accurate capacity and functionality needed for each demand period (DP), a reconfigurable manufacturing system (RMS) is able to change its configuration with time. For the RMS with multi-part flow line configuration that concurrently produces multiple parts within the same family, the cost and delivery time are dependent on its configuration and relating scheduling for any DP. So far, the study on solution method for the integrated optimisation problem of configuration design and scheduling for RMS is scarce. To efficiently find solutions with tradeoffs between total cost and tardiness, a multi-objective particle swarm optimisation (MoPSO) based on crowding distance and external Pareto solution archive is presented to solve practical-sized problems. The devised encoding and decoding methods along with the particle updating mechanism of MoPSO ensure any particle a feasible solution. The comparison between MoPSO and ε-constraint method versus small-sized cases illustrates the effectiveness of MoPSO. The comparative results between MoPSO and nondominated sorting genetic algorithm II (NSGA-II) against eight problems show that the MoPSO outperforms the NSGA-II in both solution quality and computation efficiency for the integrated optimisation problem.

Suggested Citation

  • Jianping Dou & Jun Li & Dan Xia & Xia Zhao, 2021. "A multi-objective particle swarm optimisation for integrated configuration design and scheduling in reconfigurable manufacturing system," International Journal of Production Research, Taylor & Francis Journals, vol. 59(13), pages 3975-3995, July.
    • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:13:p:3975-3995
    DOI: 10.1080/00207543.2020.1756507
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    Cited by:

    1. Sinisterra, Wilfrido Quiñones & Lima, Victor Hugo Resende & Cavalcante, Cristiano Alexandre Virginio & Aribisala, Adetoye Ayokunle, 2023. "A delay-time model to integrate the sequence of resumable jobs, inspection policy, and quality for a single-component system," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    2. Battaïa, Olga & Dolgui, Alexandre & Guschinsky, Nikolai, 2023. "MIP-based heuristics for combinatorial design of reconfigurable rotary transfer machines for production of multiple parts," International Journal of Production Economics, Elsevier, vol. 262(C).

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