Linear preselective policies for stochastic project scheduling

In the context of stochastic resource-constrained project scheduling we int roduce a novel class of scheduling policies, the linear preselective polici es. They combine the benefits of preselective policies and priority policie s; two classes that are well known from both deterministic and stochastic s cheduling. We study several properties of this new class of policies which indicate its usefulness for computational purposes. Based on a new represen tation of preselective policies as AND/OR precedence constraints we derive efficient algorithms for computing earliest job start times and state a nec essary and sufficient dominance criterion for preselective policies. A computational experiment based on 480 instances empirically validates the theoretical findings.