New benchmark results for the stochastic resource-constrained project scheduling problem

In this article* we study the stochastic resource-constrained project scheduling problem or SRCPSP, where project activities have stochastic durations. A solution is a scheduling policy, and we propose a new class of policies that is a superset of most of the existing classes that are available in the literature. A policy in this new class makes a number of a-priori decisions in a pre-processing phase while the remaining scheduling decisions are made on-line. A two-phase local-search algorithm is proposed to find high-quality policies within the class. Our computational results indicate that the proposed procedure outperforms all existing algorithms for large instances.