A cross-docking scheduling problem with sub-population multi-objective algorithms

Abstract

This paper deals with a scheduling problem of inbound and outbound trucks shipping incoming and outgoing product items into/out of a cross-docking system. We consider an instance of cross-docking systems in which more than one objective are taken into account: minimization of the total operation time (makespan) and minimization of the total lateness of outbound trucks. In order to deal with this problem, three multi-objective algorithms are developed as follows (based on the sub-population concept of evolutionary algorithms): sub-population genetic algorithm-II (SPGA-II), sub-population particle swarm optimization-II (SPPSO-II), and sub-population differential evolution algorithm-II (SPDE-II). In addition, to evaluate the performance of these algorithms, four measures are presented and compared with each other whose results will demonstrate that the SPPSO-II has better characteristics in comparison with other two algorithms.