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Flexible job-shop scheduling with flexible workdays, preemption, overlapping in operations and satisfaction criteria: an industrial application

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  • Jiae Zhang
  • Jianjun Yang

Abstract

This paper addresses a real scheduling problem, namely, a complex flexible job-shop scheduling problem (FJSP) with special characteristics (flexible workdays, preemption and overlapping in operations), where the objective is to maximise a satisfaction criterion defined through goal programming. To allow for flexible workdays, the solution representation of the classical FJSP is extended to consider overtime decisions and a sequence of time-cell states, which is used to model resource capability. A new temporal-constraint-handling method is proposed to solve the problem of overlapping in operations in a flexible-workday environment. Three solution methods are proposed to solve this scheduling problem: a heuristic method based on priority rules, a goal-guided tabu search (GGTS) and an extended genetic algorithm (EGA). In the GGTS, the neighbourhood functions are defined based on elimination approaches, and five possible neighbourhood functions ( N 0 ⊇ N 1 ⊇ N 2 ⊇ N 3 ⊇ N 4) are presented. The effectiveness and efficiency of the three solution methods are verified using dedicated benchmark instances. Computational simulations and comparisons indicate that the proposed N 4-based GGTS demonstrates performance competitive with that of the EGA and the GGTSs based on the other neighbourhood functions ( N 0, N 1, N 2 and N 3) for solving the scheduling problem.

Suggested Citation

  • Jiae Zhang & Jianjun Yang, 2016. "Flexible job-shop scheduling with flexible workdays, preemption, overlapping in operations and satisfaction criteria: an industrial application," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4894-4918, August.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:16:p:4894-4918
    DOI: 10.1080/00207543.2015.1134839
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    References listed on IDEAS

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