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Multi-machine flow shop scheduling problems with rejection using genetic algorithm

Author

Listed:
  • Mohammadreza Dabiri
  • Soroush Avakh Darestani
  • Bahman Naderi

Abstract

This work is a study on scheduling problem with rejection on a set of multi-machine in a flow-shop scheduling system. This paper will attempt to indicate development of a multi-machine flow-shop scheduling model considering rejection (this problem is NP-hard due to the NP-hardness of the same problem variation on a two-machine). We analyse the quality of a solution with two criteria: one is the make span and the one is the total rejection cost. The aim of this study is to present an approximation algorithm and three heuristic algorithms and a genetic algorithm (GA) and successfully applied to Multi-machine flow-shop scheduling model considering rejection to minimise the make span plus total rejection cost. Several tests problems were carried out to assess the performance of the proposed algorithms. We can conclude here that the GA is the most functional algorithm, followed by the approximation algorithm.

Suggested Citation

  • Mohammadreza Dabiri & Soroush Avakh Darestani & Bahman Naderi, 2019. "Multi-machine flow shop scheduling problems with rejection using genetic algorithm," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 32(2), pages 158-172.
    • Handle: RePEc:ids:ijsoma:v:32:y:2019:i:2:p:158-172
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    Citations

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    Cited by:

    1. Mosheiov, Gur & Oron, Daniel & Shabtay, Dvir, 2021. "Minimizing total late work on a single machine with generalized due-dates," European Journal of Operational Research, Elsevier, vol. 293(3), pages 837-846.
    2. Mohamadreza Dabiri & Mehdi Yazdani & Bahman Naderi & Hassan Haleh, 2022. "Modeling and solution methods for hybrid flow shop scheduling problem with job rejection," Operational Research, Springer, vol. 22(3), pages 2721-2765, July.
    3. Matan Atsmony & Gur Mosheiov, 2023. "Scheduling to maximize the weighted number of on-time jobs on parallel machines with bounded job-rejection," Journal of Scheduling, Springer, vol. 26(2), pages 193-207, April.
    4. Baruch Mor & Gur Mosheiov, 2022. "Single machine scheduling to maximize the weighted number of on-time jobs with job-rejection," Operational Research, Springer, vol. 22(3), pages 2707-2719, July.

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