A hybrid meta-heuristic algorithm for vehicle routing and packing problem with cross-docking

Abstract

Cross-docking is a relatively new logistics strategy that has a great potential to eliminate storage cost and speed up the product flows. This paper considers the vehicle routing and packing problem with cross-docking and presents a mixed integer linear mathematical model. In the model, a set of trucks are used to transport products from suppliers to customers through cross-docking centers. Each supplier and customer node can be visited only once and directly shipping is not allowed from suppliers to customers. Moreover, truck capacities are identified with physical dimensional limits on the contrary of weight or amount of load. The objective of the study is to determine the vehicle routes that minimize the total distance. Due to the complexity of the mathematical model, a hybrid meta-heuristic algorithm (HMA), which integrates tabu search (TS) algorithm within simulated annealing (SA) algorithm, is proposed to solve the problem. Proposed HMA is tested on a well-known benchmark problem data set and compared with the SA and TS solutions. Results show that proposed HMA can produce effective solutions and outperforms the SA and TS especially for the large-sized problems.