A Genetic Algorithm for the Multi-Mode Resource-Constrained Project Scheduling Problem

In this paper we present a genetic algorithm for the multi-mode resource-constrained project scheduling problem (MRCPSP), in which multiple execution modes are available for each of the activities of the project. In contrast to a conventional genetic algorithm, we apply a bi-population genetic algorithm, which makes use of two seperate populations. We extend the serial schedule generation scheme by introducing a mode optimization procedure.We present detailed comparative computational results, which reveals that our procedure is among the most competitive algorithms for the MRCPSP.