An Optimization Model and Algorithm for Heterogeneous Vehicle Routing Problem of Supermarket Distribution Considering the Characteristics of Goods

To address the issues of insufficient optimization of delivery route planning, low accuracy in matching goods characteristics with multiple types of vehicles, and high delivery costs in the supermarket delivery process caused by diverse goods characteristics and road traffic restrictions, this study investigates the heterogeneous vehicle routing problem with time window considering the characteristics of goods. This paper takes into account the special requirements of goods, including vehicle types, road restrictions, changes in vehicle fuel consumption during transportation, and other factors. It incorporates parameters for goods characteristics and integrates the matching relationship constraints between goods characteristics and the types of delivery vehicles to construct an integer programming model. An improved Immune Genetic Algorithm is proposed to address the issue by designing a coding and encoding strategy for path segmentation and vehicle selection based on goods and time window; combining with a variety of mutation operators in a variable neighborhood descent process to improve the local search ability, and adding a suboptimal solution retention mechanism to enhance the diversity of the population. The improved algorithm is used to solve the supermarket distribution plan of a logistics company in Beijing. Compared with Hybrid Particle Swarm Optimization, Genetic Algorithm, and Immune Genetic Algorithm, the cost decreases by 2.24%, 3.03%, and 4.82%, and the numbers of vehicles are decreased by 1, 1, and 2. The experiment results with the extension instance show that the cost decreases by 0.35%, 15.99%, and 16.14%, and the numbers of vehicles are decreased by 1, 3, and 2. Finally, the different combination of mutation operators is analyzed, and the results reveal that the introduced 3-opt and move operators are beneficial for the performance of the algorithm, and the different combination of operators performs various effects. Therefore, it is necessary to select a combination of operators based on the actual needs of the enterprise in practice.