We consider the dynamic stochastic resource-constrained multi-project scheduling problem where projects arrive stochastically over time. Each arriving project is of the type as considered in the stochastic resource-constrained project scheduling problem (SRCPSP). Activities are started based on a policy of priorities for all unscheduled tasks. Policies are updated at each project arrival and are chosen under the objective of minimizing the average expected flow time of the projects. We report on a computational study in which we compare several variants of a Genetic Algorithm.
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