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A sensitivity analysis to assess the completion time deviation for multi-purpose machines facing demand uncertainty

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  • André Rossi
  • Alexis Aubry
  • Mireille Jacomino

Abstract

This paper addresses multi-purpose machine configuration in an uncertain context through sensitivity analysis. The so-called configuration is the machine’s ability to process products, and the uncertain context is modelled as a demand variation affecting the forecast demand. Given a configuration, this work aims at assessing the completion time deviation when the workshop demand is subject to perturbation. Such quantitative information can be used in a robustness approach for selecting the most appropriate configuration. To do so, the configuration impact on the completion time value that can be reached by solving the attached scheduling problem is first investigated. Then, the completion time deviation is written as a piecewise linear function of the magnitude of demand variation. The proposed approach, which is based on the solution of a set of linear programs, is illustrated through a detailed example. It is shown to be polynomial, and fast enough for addressing real-world instances. Finally, how to compare two configurations on the basis of completion time deviation in an uncertain context is demonstrated. Copyright Springer Science+Business Media, LLC 2011

Suggested Citation

  • André Rossi & Alexis Aubry & Mireille Jacomino, 2011. "A sensitivity analysis to assess the completion time deviation for multi-purpose machines facing demand uncertainty," Annals of Operations Research, Springer, vol. 191(1), pages 219-249, November.
    • Handle: RePEc:spr:annopr:v:191:y:2011:i:1:p:219-249:10.1007/s10479-011-0996-y
    DOI: 10.1007/s10479-011-0996-y
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    References listed on IDEAS

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    1. Peter Brucker & Bernd Jurisch & Andreas Krämer, 1997. "Complexity of scheduling problems with multi-purpose machines," Annals of Operations Research, Springer, vol. 70(0), pages 57-73, April.
    2. Leung, Joseph Y.-T. & Li, Chung-Lun, 2008. "Scheduling with processing set restrictions: A survey," International Journal of Production Economics, Elsevier, vol. 116(2), pages 251-262, December.
    3. Jinwen Ou & Joseph Y.‐T. Leung & Chung‐Lun Li, 2008. "Scheduling parallel machines with inclusive processing set restrictions," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(4), pages 328-338, June.
    4. Penz, B. & Rapine, C. & Trystram, D., 2001. "Sensitivity analysis of scheduling algorithms," European Journal of Operational Research, Elsevier, vol. 134(3), pages 606-615, November.
    5. Aubry, A. & Rossi, A. & Espinouse, M.-L. & Jacomino, M., 2008. "Minimizing setup costs for parallel multi-purpose machines under load-balancing constraint," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1115-1125, June.
    6. Kouvelis, Panagiotis & Kurawarwala, Abbas A. & Gutierrez, Genaro J., 1992. "Algorithms for robust single and multiple period layout planning for manufacturing systems," European Journal of Operational Research, Elsevier, vol. 63(2), pages 287-303, December.
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    Cited by:

    1. Leung, Joseph Y.-T. & Li, Chung-Lun, 2016. "Scheduling with processing set restrictions: A literature update," International Journal of Production Economics, Elsevier, vol. 175(C), pages 1-11.

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