Two-stage optimisation method for material flow and allocation management in cross-docking networks

Abstract

Cross-docking is a relatively new logistics strategy in which items are moved from suppliers to customers through cross-docking centres without putting them into long-term storage. An important decision during the planning of cross-docking operations is related to the material flow management in the network, which has great potential to reduce transportation costs. However, until now, there has been a lack of studies regarding operations for both transportation of trucks between locations and trans-shipment of items in cross-docking centres. This study presents a novel two-stage mixed integer linear mathematical model for the transportation problem of cross-docking network design integrated with truck-door assignments to minimise total transportation costs from suppliers to customers. This model also considers incoming/outgoing truck-loading plans and product allocations in the cross-docking area with regard to the two-dimensional physical constraints. Due to the complexity of the problem, a genetic algorithm (GA) is proposed to solve large-sized problems. Computational studies are conducted to examine the validity of the two-stage model and performance of the GA. The computational studies show that the introduced model provides a comprehensive plan for material flow management in cross-docking networks and proposed GA is capable of obtaining effective results for the problem within a short computational time.