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Scheduling rules for two-stage flexible flow shop scheduling problem subject to tail group constraint

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  • Li, Zhan-tao
  • Chen, Qing-xin
  • Mao, Ning
  • Wang, Xiaoming
  • Liu, Jianjun

Abstract

This paper considers a two-stage flexible flow shop scheduling problem with task tail group constraint, where the two stages are made up of unrelated parallel machines. The objective is to find a schedule to minimize the total tardiness of jobs. For this problem, a mathematical model is formulated. Through analyzing this kind of problem, it is proved to be NP-hard and an advantage scheduling rule is proposed. According to the advantage scheduling rule, a new heuristic method called EL algorithm, is designed to solve this problem. From the theoretical analysis of EL algorithm, we provide EL algorithm with the time complexity and worst-case analysis. To test the performance of EL algorithm, a computational experiment is designed. In the computational experiment, both the twelve dispatching rules based on the literatures and EL algorithm are applied to the benchmark instances. Simulation results indicate that LPT–CDS, SPT–Pal, SPT–CDS and EL algorithms are effective and EL algorithm outperforms the other twelve dispatching rules with respect to the two-stage flexible flow shop scheduling problem proposed in this paper.

Suggested Citation

  • Li, Zhan-tao & Chen, Qing-xin & Mao, Ning & Wang, Xiaoming & Liu, Jianjun, 2013. "Scheduling rules for two-stage flexible flow shop scheduling problem subject to tail group constraint," International Journal of Production Economics, Elsevier, vol. 146(2), pages 667-678.
    • Handle: RePEc:eee:proeco:v:146:y:2013:i:2:p:667-678
    DOI: 10.1016/j.ijpe.2013.08.020
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    References listed on IDEAS

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    1. Bozorgirad, Mir Abbas & Logendran, Rasaratnam, 2013. "Bi-criteria group scheduling in hybrid flowshops," International Journal of Production Economics, Elsevier, vol. 145(2), pages 599-612.
    2. Logendran, Rasaratnam & Nudtasomboon, Nudtapon, 1991. "Minimizing the makespan of a group scheduling problem: a new heuristic," International Journal of Production Economics, Elsevier, vol. 22(3), pages 217-230, December.
    3. Brah, Shaukat A. & Loo, Luan Luan, 1999. "Heuristics for scheduling in a flow shop with multiple processors," European Journal of Operational Research, Elsevier, vol. 113(1), pages 113-122, February.
    4. Lin, Hung-Tso & Liao, Ching-Jong, 2003. "A case study in a two-stage hybrid flow shop with setup time and dedicated machines," International Journal of Production Economics, Elsevier, vol. 86(2), pages 133-143, November.
    5. Almeder, Christian & Hartl, Richard F., 2013. "A metaheuristic optimization approach for a real-world stochastic flexible flow shop problem with limited buffer," International Journal of Production Economics, Elsevier, vol. 145(1), pages 88-95.
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    Cited by:

    1. Marco Schulze & Julia Rieck & Cinna Seifi & Jürgen Zimmermann, 2016. "Machine scheduling in underground mining: an application in the potash industry," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(2), pages 365-403, March.
    2. Gerstl, Enrique & Mosheiov, Gur, 2014. "A two-stage flexible flow shop problem with unit-execution-time jobs and batching," International Journal of Production Economics, Elsevier, vol. 158(C), pages 171-178.

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