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A novel branch-and-bound algorithm for the chance-constrained resource-constrained project scheduling problem

Tijdschriftbijdrage - Tijdschriftartikel

© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. The resource-constrained project scheduling problem (RCPSP) has been widely studied during the last few decades. In real-world projects, however, not all information is known in advance and uncertainty is an inevitable part of these projects. The chance-constrained resource-constrained project scheduling problem (CC-RCPSP) has been recently introduced to deal with uncertainty in the RCPSP. In this paper, we propose a branch-and-bound (B&B) algorithm and a mixed integer linear programming (MILP) formulation that solve a sample average approximation of the CC-RCPSP. We introduce two different branching schemes and eight different priority rules for the proposed B&B algorithm. The computational results suggest that the proposed B&B procedure clearly outperforms both a proposed MILP formulation and a branch-and-cut algorithm from the literature.
Tijdschrift: International Journal of Production Research
ISSN: 0020-7543
Issue: 4
Volume: 57
Pagina's: 1265 - 1282
Jaar van publicatie:2019
BOF-keylabel:ja
IOF-keylabel:ja
BOF-publication weight:10
CSS-citation score:2
Authors from:Higher Education
Toegankelijkheid:Open