Resource constrained project scheduling with uncertain activity durations

Abstract

In this paper, we consider Resource Constrained Project Scheduling Problems (RCPSPs) with known deterministic renewable resource requirements but uncertain activity durations. In this case, the activity durations are represented by random variables with different probability distribution functions. To deal with this problem, we propose an approach based on the robust optimization concept, which produces reasonably good solutions under any likely input data scenario. Depending on different uncertainty characteristics, we have developed six different heuristics to incorporate the uncertain duration as a deterministic constraint in a robust optimization model. The resulting optimization model is then solved by using a Coin-Branch & Cut (CBC) solver. To judge the performance of the algorithm, we solved 30, 60, 90 and 120-activity benchmark problems from the project scheduling problem library (PSPLIB). Our proposed approach guarantees the feasibility of solutions and produces high-quality solutions, particularly for larger activity instances, compared to other existing approaches.