Abstract
This paper aims to study the optimization of chemical logistics site selection through the improved ant colony optimization algorithm. Specifically, by integrating a number of domestic and foreign literatures, this paper built an improved ant colony optimization model to assign customers of different sizes, calculated the operating costs of the chemical logistics distribution center through relevant financial indicators, and then presented an optimization plan for chemical logistics site selection. Results have shown that the optimization of chemical logistics site selection based on the improved ant colony optimization can shorten the delivery time. It is concluded that the improved ant colony optimization model can provide sound solutions for site selection of large-scale chemical logistics with a complex logistics chain, and thus can be highly promoted and widely applied.
