A simulation-based genetic algorithm for a semi-automated warehouse scheduling problem with processing time variability

Sander Teck, Reginald Dewil, Pieter Vansteenwegen

Abstract: Highlights•We present a proactive evolutionary algorithm for the stochastic RMFS scheduling problem.•We consider the integrated scheduling problem with processing variability.•We implement efficient evaluation, resource allocation and variance reduction procedures.•We evaluate the performance of the algorithm on instances with increasing due date tightness.•The proactive algorithm can generate robust and good quality schedules under uncertainty.