Intelligent pickup and delivery collocation for logistics models

Abstract

In the context of sharing economy, logistics companies have begun to adopt a new collection and distribution model based on external vehicles, and external vehicles are used to provide customers with collection/distribution services. A kind of Multi-Vehicle Split Pickup and Delivery Problem with Time Windows (MVSPDPTW) is studied in the paper. The minimum total length of the vehicle’s travel path is the objective function, and a mixed-integer linear programming model is established. A high-efficiency Tabu Simulated Annealing (TSA) algorithm is proposed. Two new neighborhood search operators are designed in the algorithm, they are used to repair the violation of capacity constraints and the operation of car replacement. In the method, the neighborhood search range is expanded and the algorithm is avoided from falling into a local optimum. In addition, a taboo mechanism and a penalty mechanism for violation of constraints are added to the algorithm, the effective tailoring of the search space is realized and the algorithm’s global optimization ability is improved. Finally, a large number of simulation experiments were performed on the algorithm based on the Solomon data set and the constructed simulation data set, and the effectiveness of the algorithm is verified in the experiments.