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A simplified swarm optimization algorithm to minimize makespan on non-identical parallel machines with unequal job release times under non-renewable resource constraints

Author

Listed:
  • Jianfu Chen

    (Hefei University of Technology
    Université Gustave-Eiffel)

  • Kai Li

    (Hefei University of Technology
    Ministry of Education)

  • Chengbin Chu

    (Université Gustave-Eiffel)

  • Abderrahim Sahli

    (Université Gustave-Eiffel)

Abstract

This article studies a uniform parallel machine scheduling problem with unequal job release times. It is assumed that each machine consumes a certain non-renewable resource when manufacturing jobs. The objective is to find an optimal schedule to minimize the makespan, given that the total resource consumption does not exceed the given limit. A mathematical model is first built to derive optimal solutions for small-scale instances. For large-scale instances, a simplified swarm optimization (SSO) algorithm is proposed. Considering that the parameters of meta-heuristic algorithms have great impacts on the output solution, the Taguchi method is then applied to tune the algorithm parameters. Afterward, a large number of simulation experiments are conducted. Finally, Friedman’s test and Wilcoxon signed-rank test are employed to analyze the simulation results from statistical perspectives. Experimental results reveal that the proposed algorithm can provide competitive solutions.

Suggested Citation

  • Jianfu Chen & Kai Li & Chengbin Chu & Abderrahim Sahli, 2024. "A simplified swarm optimization algorithm to minimize makespan on non-identical parallel machines with unequal job release times under non-renewable resource constraints," Operational Research, Springer, vol. 24(2), pages 1-27, June.
    • Handle: RePEc:spr:operea:v:24:y:2024:i:2:d:10.1007_s12351-024-00829-6
    DOI: 10.1007/s12351-024-00829-6
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