Scheduling trucks and assigning them to dock doors are two major operational decisions in cross-dock facilities. Literature and practice often consider these problems sequentially, or only for inbound or outbound operations. In this paper, we integrate the scheduling and assignment problem at cross-dock terminals for both inbound and outbound operations. The objective of the problem is to minimize delay costs of outbound trucks, costs of temporary storage (in case the designated outbound truck is not docked at the same time as the inbound truck), and costs of direct dock-to-dock transfers (which is proportional to the distance between the assigned dock doors). We do so while considering numerous characteristics of cross-dock terminals prevalent in practice but often ignored in literature, such as flexible dock doors and predetermined truck processing time windows. We develop a mathematical model and a metaheuristic based on Adaptive Large Neighborhood Search to solve real-sized instances. Extensive computational experiments demonstrate that the algorithm produces high quality solutions compared to existing sequential approaches within reasonable computational times (particularly for large instances). We also use the metaheuristic to plan the cross-dock operations of a retailer in a case study, and demonstrate that significant savings can be generated by adopting the metaheuristic as planning tool. (Co-authors: Marco Bijvank, René de Koster)
Arpan Rijal is a third-year PhD student at the Department of Technology and Operations Management, Rotterdam School of Management, Erasmus University. His research focuses on warehousing management and logistics planning. He is particularly interested in translating practical optimization problems at the intersection of warehousing and distribution into mathematical models and developing efficient solution methodologies for them. Before joining Erasmus University, he obtained his MSc in International Logistics from Jacobs University, Bremen, Germany.
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