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Robust Optimization for the Resource-Constrained Project Scheduling Problem with Duration Uncertainty

In: Handbook on Project Management and Scheduling Vol. 2

Author

Listed:
  • Christian Artigues

    (Univ de Toulouse)

  • Roel Leus

    (KU Leuven)

  • Fabrice Talla Nobibon

    (FedEx Europe)

Abstract

In this chapter, we examine the RCPSP for the case when there is considerable uncertainty in the activity durations, to the extent that the decision maker cannot with confidence associate probabilities with the possible outcomes of a decision. Our modeling techniques stem from robust discrete optimization, which is a theoretical framework that enables the decision maker to produce solutions that will have a reasonably good objective value under any likely input data scenario. We develop and implement a scenario-relaxation algorithm and a scenario-relaxation-based heuristic. The first algorithm produces optimal solutions but requires excessive running times even for medium-sized instances; the second algorithm produces high-quality solutions for medium-sized instances and outperforms two benchmark heuristics.

Suggested Citation

  • Christian Artigues & Roel Leus & Fabrice Talla Nobibon, 2015. "Robust Optimization for the Resource-Constrained Project Scheduling Problem with Duration Uncertainty," International Handbooks on Information Systems, in: Christoph Schwindt & Jürgen Zimmermann (ed.), Handbook on Project Management and Scheduling Vol. 2, edition 127, chapter 0, pages 875-908, Springer.
    • Handle: RePEc:spr:ihichp:978-3-319-05915-0_10
    DOI: 10.1007/978-3-319-05915-0_10
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    Cited by:

    1. Farnaz Torabi Yeganeh & Seyed Hessameddin Zegordi, 2020. "A multi-objective optimization approach to project scheduling with resiliency criteria under uncertain activity duration," Annals of Operations Research, Springer, vol. 285(1), pages 161-196, February.

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