New competitive results for the stochastic resource‐constrained project scheduling problem: exploring the benefits of pre‐processing

We study the resource‐constrained project scheduling problem with stochastic activity durations. We introduce a new class of scheduling policies for solving this problem, which make a number of a‐priori sequencing decisions in a pre‐processing phase while the remaining decisions are made dynamically during project execution. The pre‐processing decisions entail the addition of extra precedence constraints to the scheduling instance, hereby resolving some potential resource conflicts. We obtain new competitive results for expected‐makespan minimization on representative datasets, which are significantly better than those obtained by the existing algorithms when the variability in the activity durations is medium to high.