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

Jianfu Chen, Kai Li (), Chengbin Chu and Abderrahim Sahli
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Jianfu Chen: Hefei University of Technology
Kai Li: Hefei University of Technology
Chengbin Chu: Université Gustave-Eiffel
Abderrahim Sahli: Université Gustave-Eiffel

Operational Research, 2024, vol. 24, issue 2, No 9, 27 pages

Abstract: 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.

Keywords: Parallel machine scheduling; Resource consumption; Simplified swarm optimization; Makespan (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s12351-024-00829-6

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