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Scheduling the two-machine flowshop to hedge against processing time uncertainty

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  • Kuo-Ching Ying

    (National Taipei University of Technology, Taipei, Taiwan)

Abstract

This paper addresses the two-machine flowshop scheduling problem with uncertain job processing times. It is assumed that in the realization of a schedule, job processing times may take any values from their corresponding intervals given before scheduling. The objective is to determine a robust schedule with the minimum makespan of the restricted worst-case scenario among all possible scenarios to hedge against processing time uncertainty for a given number of jobs. We formulate the problem of interest as a robust counterpart optimization model, and apply a simulated annealing (SA) algorithm and an iterated greedy (IG) algorithm to solve it. The experimental results show that both algorithms are effective in determining robust schedules for small-size problems, while the IG algorithm is more effective than the SA algorithm for large-size problems, albeit at the expense of more computational time.

Suggested Citation

  • Kuo-Ching Ying, 2015. "Scheduling the two-machine flowshop to hedge against processing time uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(9), pages 1413-1425, September.
    • Handle: RePEc:pal:jorsoc:v:66:y:2015:i:9:p:1413-1425
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    Cited by:

    1. Levorato, Mario & Figueiredo, Rosa & Frota, Yuri, 2022. "Exact solutions for the two-machine robust flow shop with budgeted uncertainty," European Journal of Operational Research, Elsevier, vol. 300(1), pages 46-57.
    2. Mario Levorato & David Sotelo & Rosa Figueiredo & Yuri Frota, 2024. "Efficient solutions to the m-machine robust flow shop under budgeted uncertainty," Annals of Operations Research, Springer, vol. 338(1), pages 765-799, July.

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