An effective metaheuristic algorithm for flowshop scheduling with deteriorating jobs

Hongfeng Wang (), Min Huang and Junwei Wang
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Hongfeng Wang: Northeastern University
Min Huang: Northeastern University
Junwei Wang: The University of Hong Kong

Journal of Intelligent Manufacturing, 2019, vol. 30, issue 7, No 12, 2733-2742

Abstract: Abstract The deterioration effect in flowshop scheduling has gained a growing concern from the community of operational research in recent years. However, all of existing studies focus on two- or three-machine flow shops. In this paper, a m-machine $$(m>3)$$ ( m > 3 ) flowshop scheduling problem (FSSP) with deteriorating jobs is investigated and a novel metaheuristic algorithm called multi-verse optimizer (MVO) is employed to solve it. The MVO algorithm can accomplish the optimization process via exchanging objects of universes through white/black hole and wormhole tunnels. In the novel MVO algorithm, a new elitist selection scheme is designed to construct the effective white/black hole tunnels, whereas two different local search operators are hybridized and embedded to further enhance the exploitation capability. Experimental results indicate that the proposed algorithm can achieve the satisfactory performance in solving the investigated FSSP with deteriorating jobs.

Keywords: Scheduling; Flowshop scheduling; Deterioration; Metaheuristic algorithm; Multi-verse optimizer (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10845-018-1425-8

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