Generating Proactive Execution Policies for Resource-Constrained Projects with Uncertain Activity Durations

The resource-constrained project scheduling problem involves the determination of a schedule of the project activities, satisfying the precedence relations and resource constraints while minimizing the project duration. In practice, activity durations may be subject to variability, such that a stochastic approach to the problem is more appropriate. We propose a methodology for the determination of a project execution policy and a vector of predictive activity starting times with the objective of minimizing a cost function that consists of the weighted expected activity starting time deviations and the penalties or bonuses associated with late or early project completion. In a computational experiment, we show that our procedure greatly outperforms existing algorithms described in the literature