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A dynamic differential evolution algorithm for the dynamic single-machine scheduling problem with sequence-dependent setup times

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  • Yue Zhao
  • Gongshu Wang

Abstract

The paper studies the single-machine scheduling problem with sequence-dependent setup times under dynamic environment. In this problem, jobs arrive over time and all the information on a job is unknown in advance. The objective is to find a feasible schedule such that the maximum lateness is minimised. This problem represents a very important production scheduling problem but remains under-represented in the literature. To solve the problem, we propose a dynamic differential evolution algorithm that considers the new environment and the previous environment simultaneously. The performance of the algorithm is enhanced by two heuristics for generating efficient initial solutions, a local search procedure and a speed-up method. To evaluate its performance, the proposed algorithm is tested on 1000 instances from the literature. The computational results demonstrate that the proposed algorithm is highly effective as compared to the methods known from the literature.

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  • Yue Zhao & Gongshu Wang, 2020. "A dynamic differential evolution algorithm for the dynamic single-machine scheduling problem with sequence-dependent setup times," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(2), pages 225-236, February.
    • Handle: RePEc:taf:tjorxx:v:71:y:2020:i:2:p:225-236
    DOI: 10.1080/01605682.2019.1596591
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    Cited by:

    1. Xiuli Wu & Junjian Peng & Xiao Xiao & Shaomin Wu, 2021. "An effective approach for the dual-resource flexible job shop scheduling problem considering loading and unloading," Journal of Intelligent Manufacturing, Springer, vol. 32(3), pages 707-728, March.

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