Real Traffic Distance-Aware Logistics Scheduling

Logistics scheduling is an important issue in nowadays smart city construction because the scheduling results can determine the efficiency of logistics distribution, and thus influence the development of logistics companies. Although many remarkable works attempted to solve the logistics scheduling problems, especially the logistics-related vehicle routing problem (VRP), most of them established the models based on Euclidean distance, which may result in suboptimal solutions due to the ignorance of road layout. That is, the optimal solution of the model may be suboptimal or even impractical when applied to the real-world situation because of the difference between the model and the real situation. To deal with this weakness, a VRP-based real traffic distance-aware logistics scheduling model that considers the road layout is established in this paper, where the real traffic distance is used as the input of the model. With the assistance of Baidu Map API, the real traffic distance between any two locations and the real traffic duration between them can be captured. In this way, a problem instance set with three scales (i.e., with 20, 30, and 40 locations) is built up for experiments. Besides, the ant colony system (ACS) is employed to solve the problem instances under the cases of using Euclidean distance, linear distance, and real traffic distance to measure the solutions. Comparison results from perspectives of both real traffic distance and real traffic duration show the better performance of solutions obtained under the case of real traffic distance.