A cross-docking scheduling problem with sub-population multi-objective algorithms |
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Authors: | A. Boloori Arabani M. Zandieh S. M. T. Fatemi Ghomi |
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Affiliation: | 1. Department of Industrial and Systems Engineering, Wayne State University, 4815 Fourth Street, Detroit, MI, 48202, USA 2. Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, G.C., Tehran, Iran 3. Department of Industrial Engineering, Amirkabir University of Technology, 424 Hafez Avenue, Tehran, Iran
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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. |
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