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

Morteza Davari and Erik Demeulemeester

International Journal of Production Research, 2019, vol. 57, issue 4, 1265-1282

Abstract: 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.

Date: 2019
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DOI: 10.1080/00207543.2018.1504245

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