Research on last-mile logistics route optimization based on an improved ant colony algorithm

Rural e-commerce logistics serves as a critical material foundation for the development of rural e-commerce. However, due to its long transportation distances and low population density among consumer groups, the cost-benefit efficiency of rural e-commerce logistics remains suboptimal. To enhance cost-effectiveness, this paper proposes an optimization model for last-mile delivery in rural e-commerce logistics and employs an improved ant colony algorithm to solve the model. Through multiple sets of test data, the optimal parameter configurations of the ant colony algorithm under different node scales are determined. Additionally, a case study is conducted to validate the effectiveness of the proposed model and algorithm. The results demonstrate that the improved algorithm can provide practical and feasible last-mile delivery route solutions for rural e-commerce logistics, offering strong support for addressing last-mile delivery challenges in this context.