A discrete differential evolution algorithm for flow shop group scheduling problem with sequence-dependent setup and transportation times

Shuaipeng Yuan (), Tieke Li and Bailin Wang
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Shuaipeng Yuan: University of Science and Technology Beijing
Tieke Li: University of Science and Technology Beijing
Bailin Wang: University of Science and Technology Beijing

Journal of Intelligent Manufacturing, 2021, vol. 32, issue 2, No 7, 427-439

Abstract: Abstract This study investigates a flow shop group scheduling problem where both sequence-dependent setup time between groups and round-trip transportation time between machines are considered. The objective is to minimize makespan. To solve the problem, we first develop a mixed integer linear programming model and then propose an efficient co-evolutionary discrete differential evolution algorithm (CDDEA). In the CDDEA, several problem-specific heuristic rules are generated to construct initial population. A novel discrete differential evolution mechanism and a cooperative-oriented optimization strategy are proposed to synergistically evolve both the sequence of jobs in each group and the sequence of groups. In addition, two lower bounds are developed to evaluate the solution quality of CDDEA. Extensive computational experiments are carried out. The results show that the proposed CDDEA is effective in solving the studied problem.

Keywords: Flow shop group scheduling; Sequence-dependent setup time; Round-trip transportation time; Discrete differential evolution; Cooperative-oriented optimization (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10845-020-01580-3

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