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Minimising maximum tardiness in assembly flowshops with setup times

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  • Asiye Aydilek
  • Harun Aydilek
  • Ali Allahverdi

Abstract

This paper addresses a two-stage assembly flowshop scheduling problem with the objective of minimising maximum tardiness where set-up times are considered as separate from processing times. The performance measure of maximum tardiness is important for some scheduling environments, and hence, it should be taken into account while making scheduling decisions for such environments. Given that the problem is strongly NP-hard, different algorithms have been proposed in the literature. The algorithm of Self-Adaptive Differential Evolution (SDE) performs as the best for the problem in the literature. We propose a new hybrid simulated annealing and insertion algorithm (SMI). The insertion step, in the SMI algorithm, strengthens the exploration step of the simulated annealing algorithm at the beginning and reinforces the exploitation step of the simulated annealing algorithm towards the end. Furthermore, we develop several dominance relations for the problem which are incorporated in the proposed SMI algorithm. We compare the performance of the proposed SMI algorithm with that of the best existing algorithm, SDE. The computational experiments indicate that the proposed SMI algorithm performs significantly better than the existing SDE algorithm. More specifically, under the same CPU time, the proposed SMI algorithm, on average, reduces the error of the best existing SDE algorithm over 90%, which indicates the superiority of the proposed SMI algorithm.

Suggested Citation

  • Asiye Aydilek & Harun Aydilek & Ali Allahverdi, 2017. "Minimising maximum tardiness in assembly flowshops with setup times," International Journal of Production Research, Taylor & Francis Journals, vol. 55(24), pages 7541-7565, December.
  • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:24:p:7541-7565
    DOI: 10.1080/00207543.2017.1387300
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    Citations

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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.
    2. Zikai Zhang & Qiuhua Tang, 2022. "Integrating preventive maintenance to two-stage assembly flow shop scheduling: MILP model, constructive heuristics and meta-heuristics," Flexible Services and Manufacturing Journal, Springer, vol. 34(1), pages 156-203, March.
    3. Ana Rita Antunes & Marina A. Matos & Ana Maria A. C. Rocha & Lino A. Costa & Leonilde R. Varela, 2022. "A Statistical Comparison of Metaheuristics for Unrelated Parallel Machine Scheduling Problems with Setup Times," Mathematics, MDPI, vol. 10(14), pages 1-19, July.
    4. Framinan, Jose M. & Perez-Gonzalez, Paz & Fernandez-Viagas, Victor, 2019. "Deterministic assembly scheduling problems: A review and classification of concurrent-type scheduling models and solution procedures," European Journal of Operational Research, Elsevier, vol. 273(2), pages 401-417.

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