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Interstage Transportation Planning in the Deterministic Flow-Shop Environment

Author

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  • Michael A. Langston

    (Washington State University, Pullman, Washington)

Abstract

In the well-known flow-shop model, we are given a k -stage processing facility and a collection of jobs, each comprising k tasks to be processed in order, one per stage. At every stage, one or more machines are available for processing tasks. We assume that the jobs are independent and that the processing of a task, once begun, cannot be interrupted. In this paper we focus our attention on a critical but largely ignored aspect of flow-shop utilization, namely, that of planning the efficient transportation of work between stages. We therefore assume the existence of a transport, used to ferry jobs from one stage to the next. We devise and formally analyze effective transportation strategies for various situations in this environment that are dependent on the amount of time needed for transportation relative to the amount required for task processing.

Suggested Citation

  • Michael A. Langston, 1987. "Interstage Transportation Planning in the Deterministic Flow-Shop Environment," Operations Research, INFORMS, vol. 35(4), pages 556-564, August.
    • Handle: RePEc:inm:oropre:v:35:y:1987:i:4:p:556-564
    DOI: 10.1287/opre.35.4.556
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    Citations

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    Cited by:

    1. Li, Shanling, 1997. "A hybrid two-stage flowshop with part family, batch production, major and minor set-ups," European Journal of Operational Research, Elsevier, vol. 102(1), pages 142-156, October.
    2. Hurink, Johann & Knust, Sigrid, 2005. "Tabu search algorithms for job-shop problems with a single transport robot," European Journal of Operational Research, Elsevier, vol. 162(1), pages 99-111, April.
    3. Haiyan Wang & Chung‐Yee Lee, 2005. "Production and transport logistics scheduling with two transport mode choices," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(8), pages 796-809, December.
    4. Chung‐Lun Li & Jinwen Ou, 2005. "Machine scheduling with pickup and delivery," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(7), pages 617-630, October.
    5. Joseph Leung & Hairong Zhao, 2008. "Scheduling problems in master-slave model," Annals of Operations Research, Springer, vol. 159(1), pages 215-231, March.
    6. Li, Chung-Lun & Vairaktarakis, George & Lee, Chung-Yee, 2005. "Machine scheduling with deliveries to multiple customer locations," European Journal of Operational Research, Elsevier, vol. 164(1), pages 39-51, July.
    7. Ann Vandevelde & Han Hoogeveen & Cor Hurkens & Jan Karel Lenstra, 2005. "Lower Bounds for the Head-Body-Tail Problem on Parallel Machines: A Computational Study of the Multiprocessor Flow Shop," INFORMS Journal on Computing, INFORMS, vol. 17(3), pages 305-320, August.
    8. Yiyi Xu & M’hammed Sahnoun & Fouad Ben Abdelaziz & David Baudry, 2022. "A simulated multi-objective model for flexible job shop transportation scheduling," Annals of Operations Research, Springer, vol. 311(2), pages 899-920, April.

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