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