Robust optimization for the resource-constrained project scheduling problem with duration uncertainty

Christian Artigues (1) , Roel Leus (2) , Fabrice Talla Nobibon (3)

1 LAAS-ROC - Équipe Recherche Opérationnelle, Optimisation Combinatoire et Contraintes
2 ORSTAT - Operations Research and Business Statistics
3 KU Leuven - Catholic University of Leuven = Katholieke Universiteit Leuven

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.

Mots clés: Project scheduling; Robust optimization; RCPSP; Scenario relaxation; Uncertain durations

Domaines: Recherche opérationnelle [math.OC]

Christian Artigues, Roel Leus, Fabrice Talla Nobibon. Robust optimization for the resource-constrained project scheduling problem with duration uncertainty. Christoph Schwindt and Jurgen Zimmermann. Handbook on Project Management and Scheduling Vol.2, Springer International Publishing, pp.875-908, 2015, International Handbooks on Information Systems, 978-3-319-05914-3. ⟨10.1007/978-3-319-05915-0_10⟩. ⟨hal-01875875⟩