Skip to main content
Log in

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

  • Published:
Annals of Operations Research Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Abumaizar, R. J., & Svestka, J. A. (1997). Rescheduling job shops under random disruptions. International Journal of Production Research, 35(7), 2065–2082.

    Article  Google Scholar 

  • Alagöz, O., & Azizoğlu, M. (2003). Rescheduling of identical parallel machines under machine eligibility constraints. European Journal of Operational Research, 149, 523–532.

    Article  Google Scholar 

  • Aytug, H., Lawley, M. A., McKay, K., Mohan, S., & Uzsoy, R. (2005). Executing production schedules in the face of uncertainties: A review and some future directions. European Journal of Operational Research, 161, 86–110.

    Article  Google Scholar 

  • Błażewicz, J., Ecker, K., Pesch, E., Schmidt, G., & Węglarz, J. (1996). Scheduling computer and manufacturing processes. Berlin: Springer.

    Google Scholar 

  • Duenas, A., Petrovic, D., & Petrovic, S. (2005). In A. Gelbukh, A. de Albornoz, & H. Terashima-Marin (Eds.), Lecture notes in artificial intelligence, MICAI 2005: Advances in artificial intelligence (pp. 234–243). Berlin: Springer.

    Google Scholar 

  • Li, H., Li, Z., Li, L. X., & Hu, B. (2000). A production rescheduling expert simulation system. European Journal of Operational Research, 124, 283–293.

    Article  Google Scholar 

  • Mehta, S. V., & Uzsoy, R. (1999). Predictable scheduling of a single machine subject to breakdowns. International Journal of Computer Integrated Manufacturing, 12(1), 15–38.

    Article  Google Scholar 

  • O’Donovan, R., Uzsoy, R., & McKay, K. N. (1999). Predictable scheduling of a single machine with breakdown and sensitive jobs. International Journal of Production Research, 37(18), 4217–4233.

    Article  Google Scholar 

  • Panwalkar, S. S., & Iskander, W. (1977). A survey of scheduling rules. Operations Research, 25(1), 45–61.

    Article  Google Scholar 

  • Papoulis, A. (1991). Probability, random variables and stochastic processes (3rd ed.). New York: McGraw-Hill.

    Google Scholar 

  • Petrovic, D., Petrovic, R., & Vujosevic, M. (1996). Fuzzy models for the newsboy problem. International Journal of Production Economics, 45, 435–441.

    Article  Google Scholar 

  • Pinedo, M. (2002). Scheduling: Theory, algorithms, and systems. New Yrok: Prentice Hall.

    Google Scholar 

  • Rangsaritratsamee, R., Ferrell, W. G., & Kurz, M. B. (2004). Dynamic rescheduling that simultaneously considers efficiency and stability. Computers and Industrial Engineering, 46, 1–15.

    Article  Google Scholar 

  • Ruspini, E. H., Bonissone, P. P., & Pedrycz, W. (1998). Handbook of fuzzy computation. Philadelphia: Institute of Physics Publishing.

    Google Scholar 

  • Vieira, G. E., Herrmann, J. W., & Lin, E. (2003). Rescheduling manufacturing systems: A framework of strategies, policies, and methods. Journal of Scheduling, 6, 39–62.

    Article  Google Scholar 

  • Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353.

    Article  Google Scholar 

  • Zimmermann, H.-J. (1996). Fuzzy set theory and its applications (3rd ed.). Dordrecht: Kluwer Academic.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dobrila Petrovic.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Duenas, A., Petrovic, D. An approach to predictive-reactive scheduling of parallel machines subject to disruptions. Ann Oper Res 159, 65–82 (2008). https://doi.org/10.1007/s10479-007-0280-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-007-0280-3

Keywords

Navigation