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An approach to predictive-reactive scheduling of parallel machines subject to disruptions

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  • Alejandra Duenas
  • Dobrila Petrovic

Abstract

In this paper, a new predictive-reactive approach to a parallel machine scheduling problem in the presence of uncertain disruptions is presented. The approach developed is based on generating a predictive schedule that absorbs the effects of possible uncertain disruptions through adding idle times to the job processing times. The uncertain disruption considered is material shortage, described by the number of disruption occurrences and disruption repair period. These parameters are specified imprecisely and modelled using fuzzy sets. If the impact of a disruption is too high to be absorbed by the predictive schedule, a rescheduling action is carried out. This approach has been applied to solving a real-life scheduling problem of a pottery company. Copyright Springer Science+Business Media, LLC 2008

Suggested Citation

  • Alejandra Duenas & Dobrila Petrovic, 2008. "An approach to predictive-reactive scheduling of parallel machines subject to disruptions," Annals of Operations Research, Springer, vol. 159(1), pages 65-82, March.
    • Handle: RePEc:spr:annopr:v:159:y:2008:i:1:p:65-82:10.1007/s10479-007-0280-3
    DOI: 10.1007/s10479-007-0280-3
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    References listed on IDEAS

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    1. Aytug, Haldun & Lawley, Mark A. & McKay, Kenneth & Mohan, Shantha & Uzsoy, Reha, 2005. "Executing production schedules in the face of uncertainties: A review and some future directions," European Journal of Operational Research, Elsevier, vol. 161(1), pages 86-110, February.
    2. S. S. Panwalkar & Wafik Iskander, 1977. "A Survey of Scheduling Rules," Operations Research, INFORMS, vol. 25(1), pages 45-61, February.
    3. Petrovic, Dobrila & Petrovic, Radivoj & Vujosevic, Mirko, 1996. "Fuzzy models for the newsboy problem," International Journal of Production Economics, Elsevier, vol. 45(1-3), pages 435-441, August.
    4. Li, Heng & Li, Zhicheng & Li, Ling X. & Hu, Bin, 2000. "A production rescheduling expert simulation system," European Journal of Operational Research, Elsevier, vol. 124(2), pages 283-293, July.
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    Cited by:

    1. Iwona Paprocka & Bożena Skołud, 2017. "A hybrid multi-objective immune algorithm for predictive and reactive scheduling," Journal of Scheduling, Springer, vol. 20(2), pages 165-182, April.
    2. Guillermo Durand & Fernando Mele & J. Bandoni, 2012. "Determination of storage tanks location for optimal short-term scheduling in multipurpose/multiproduct batch-continuous plants under uncertainties," Annals of Operations Research, Springer, vol. 199(1), pages 225-247, October.
    3. Wang Hong Li & Liang Liang & Sonia Valeria Avilés-Sacoto & Raha Imanirad & Wade D. Cook & Joe Zhu, 2017. "Modeling efficiency in the presence of multiple partial input to output processes," Annals of Operations Research, Springer, vol. 250(1), pages 235-248, March.

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