Solving the Multi-Objective Vehicle Routing Problem with Parcel Lockers

With the development of e-commerce and urbanization, logistics distribution has become a key challenge in improving traffic management and efficiency. The use of parcel lockers can alleviate delivery pressure, enhance user experience, and reduce costs. This paper investigates the Multi-Objective Vehicle Routing Problem with Parcel Lockers (MOVRPPL), aiming to optimize transportation costs, customer satisfaction, and the number of vehicles to improve resource utilization. Based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II), this paper proposes the NSGA-II-NI algorithm, which incorporates the nearest neighbor crossover algorithm and route optimization to approximate the Pareto optimal solution set. Experiments using the Solomon dataset are conducted, and the performance is evaluated using the Inverted Generational Distance (IGD) and Hypervolume (HV), compared with the state-of-the-art algorithm NSGA-II-HI. The experimental results show that our method achieves a better balance among multiple objectives, significantly reducing transportation costs and the number of vehicles while enhancing customer satisfaction and providing superior solutions.