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Dynamic order acceptance and capacity planning in a stochastic multi-project environment with a bottleneck resource

Author

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  • Philipp Melchiors
  • Roel Leus
  • Stefan Creemers
  • Rainer Kolisch

Abstract

We study the integration of order acceptance and capacity planning in multi-project environments with dynamically arriving projects. We model this planning problem as a continuous-time Markov decision process to determine long-term optimal decisions. We examine whether macro-process planning should be performed before or after order acceptance. We characterise the structure of optimal policies, and explore the dependence on a number of parameters such as project payoff, project cost and order arrival time. We also look into the effects of set-up costs and the use of non-regular capacity.

Suggested Citation

  • Philipp Melchiors & Roel Leus & Stefan Creemers & Rainer Kolisch, 2018. "Dynamic order acceptance and capacity planning in a stochastic multi-project environment with a bottleneck resource," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 459-475, January.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:1-2:p:459-475
    DOI: 10.1080/00207543.2018.1431417
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    Cited by:

    1. Xin Li & José A. Ventura & Kevin A. Bunn, 2021. "A joint order acceptance and scheduling problem with earliness and tardiness penalties considering overtime," Journal of Scheduling, Springer, vol. 24(1), pages 49-68, February.
    2. R. Micale & C. M. La Fata & M. Enea & G. La Scalia, 2021. "Regenerative scheduling problem in engineer to order manufacturing: an economic assessment," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 1913-1925, October.
    3. Satic, U. & Jacko, P. & Kirkbride, C., 2024. "A simulation-based approximate dynamic programming approach to dynamic and stochastic resource-constrained multi-project scheduling problem," European Journal of Operational Research, Elsevier, vol. 315(2), pages 454-469.

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