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

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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.

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Acknowledgements

This research is supported by the National Natural Science Foundation of China under [Grant Number 71701016, 71471015]; and the Beijing Natural Science Foundation under [Grant Number 9174038].

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Authors and Affiliations

  1. Donlinks School of Economics and Management, University of Science and Technology Beijing, 30 Xueyuan Road, Haidian District, Beijing, 100083, People’s Republic of China

    Shuaipeng Yuan, Tieke Li & Bailin Wang

  2. Engineering Research Center of MES Technology for Iron and Steel Production, Ministry of Education, Beijing, 100083, People’s Republic of China

    Shuaipeng Yuan, Tieke Li & Bailin Wang

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  1. Shuaipeng Yuan
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  2. Tieke Li
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  3. Bailin Wang
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Correspondence to Shuaipeng Yuan.

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Yuan, S., Li, T. & Wang, B. A discrete differential evolution algorithm for flow shop group scheduling problem with sequence-dependent setup and transportation times. J Intell Manuf 32, 427–439 (2021). https://doi.org/10.1007/s10845-020-01580-3

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  • DOI: https://doi.org/10.1007/s10845-020-01580-3

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