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

Christian Artigues (), Roel Leus () and Fabrice Talla Nobibon ()
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Christian Artigues: Univ de Toulouse
Roel Leus: KU Leuven
Fabrice Talla Nobibon: FedEx Europe

Chapter Chapter 40 in Handbook on Project Management and Scheduling Vol. 2, 2015, pp 875-908 from Springer

Abstract: 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.

Keywords: Project scheduling; Robust optimization; RCPSP; Scenario relaxation; Uncertain durations (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1007/978-3-319-05915-0_10

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