Collaborative Optimization of Dock Door Assignment and Vehicle Scheduling in Cross-Docking

Abstract

Cross-docking is a logistic strategy that can transport goods directly from suppliers or manufacturers to retailers or customers. In daily life, the requirements for timeliness of goods distribution have been continuously improved. Cross-docking can realize the rapid transshipment of goods and improve the process efficiency of distribution greatly. Meanwhile, during the cross-docking process, goods are deposited in the temporary storage area, which reduces the storage cost. This paper focuses on the analysis of reasonable vehicle scheduling and dock door allocation problems in cross-docking. The goal is to minimize the working time of cross-docks by the research on this combinatorial optimization problem. This paper proposes the genetic algorithm (GA) and the hybrid particle swarm optimization to solve the three-scale (small, medium and large) cross-docks. Optimal completion time, average completion time and average solution time are considered as factors to evaluate the efficiency of two algorithms on three scales. And then the concept of mixed-mode dock door is introduced. GA is used to conduct numerical experiments with mixed dock doors on different scales. Finally, by comparing the utilization rate of mixed dock doors, we can analyze the influence of mixed dock door on vehicles’ waiting time.