Route Plan Model of Unmanned Logistic Delivery Vehicle Based on Multi-objective Optimization Algorithm

The path planning of unmanned logistics distribution vehicles is an important issue in the field of modern logistics, which directly affects cost-effectiveness, delivery time and sustainability. In order to solve this problem, a path planning model based on multi-objective optimization algorithm is proposed in this study, aiming at finding the best compromise between multiple objectives. Our model considers various constraints in reality, such as road network, vehicle capacity, time window and sustainability requirements. A multi-objective optimization algorithm based on interactive identification of decision variables (MO-IIDV) is proposed. The algorithm usually focuses on considering the relationship between decision variables in the optimization process to better search Pareto frontier. The algorithm tries to capture and use the correlation between decision variables to improve the optimization results. And apply the MO-IIDV algorithm to solve the proposed Multi-Objective Unmanned Logistics Vehicle Routing Problem (MO-ULVRP). The research results show that under the same conditions, the solution set obtained by MO-IIDV algorithm is of high quality, good robustness and fast convergence speed, and it can better optimize and solve the vehicle routing problem of urban logistics distribution, which proves the effectiveness of MO-ffDV algorithm. It is verified that this method is excellent in practical application and can provide more efficient, economical and sustainable distribution solutions for logistics companies.