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A simple two-agent system for multi-objective flexible job-shop scheduling

Author

Listed:
  • Yingli Li

    (Tongji University)

  • Jiahai Wang

    (Tongji University)

  • Zhengwei Liu

    (Tongji University)

Abstract

In this paper, a simple two-agent multi-objective scheduling system for flexible job-shop scheduling problem is proposed and corresponding framework is given. Under the framework, a broadcast communication mechanism with task mark and leader–follower control mode are designed and used to ensure orderly activities among agents. To obtain initial solution and improve it, competition and cooperation strategies are developed. To jump out of the local optimal solution and expend the search space, an adaptive iterative loop solving mechanism is designed. Three commonly used benchmark instance sets are adopted to test the performance of the proposed method. Computation results and comparison analysis with other excellent algorithms demonstrate that it is feasible and effective.

Suggested Citation

  • Yingli Li & Jiahai Wang & Zhengwei Liu, 2022. "A simple two-agent system for multi-objective flexible job-shop scheduling," Journal of Combinatorial Optimization, Springer, vol. 43(1), pages 42-64, January.
    • Handle: RePEc:spr:jcomop:v:43:y:2022:i:1:d:10.1007_s10878-021-00748-8
    DOI: 10.1007/s10878-021-00748-8
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    References listed on IDEAS

    as
    1. Wei Xiong & Dongmei Fu, 2018. "A new immune multi-agent system for the flexible job shop scheduling problem," Journal of Intelligent Manufacturing, Springer, vol. 29(4), pages 857-873, April.
    2. Manzhan Gu & Jinwei Gu & Xiwen Lu, 2018. "An algorithm for multi-agent scheduling to minimize the makespan on m parallel machines," Journal of Scheduling, Springer, vol. 21(5), pages 483-492, October.
    3. Xiuli Wu & Shaomin Wu, 2017. "An elitist quantum-inspired evolutionary algorithm for the flexible job-shop scheduling problem," Journal of Intelligent Manufacturing, Springer, vol. 28(6), pages 1441-1457, August.
    4. Chong Peng & Guanglin Wu & T Warren Liao & Hedong Wang, 2019. "Research on multi-agent genetic algorithm based on tabu search for the job shop scheduling problem," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-19, September.
    5. Muhammad Kamal Amjad & Shahid Ikramullah Butt & Rubeena Kousar & Riaz Ahmad & Mujtaba Hassan Agha & Zhang Faping & Naveed Anjum & Umer Asgher, 2018. "Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-32, February.
    Full references (including those not matched with items on IDEAS)

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