School of Logistics and Transportation, Central South University of Forestry and Technology
This work was supported by the National Natural Science Foundation, China (No. 61773120, No.71771028)。
The popularity of fresh e-commerce and cold chain home delivery makes the cold chain logistics orders present the characteristics of "small batch, multi batch, perishable", which further increases the necessity and difficulty of urban cold chain logistics distribution path optimization. In this paper, the road congestion is reflected in the speed of vehicles on the road, and the mathematical model of cold chain vehicle routing optimization is built to minimize the total cost on the basis of customer satisfaction. In order to solve this problem, a new knowledge-based ant colony algorithm is designed by integrating the tabu search operator under the knowledge-based elitist strategy and the knowledge model of dynamic probability selection into the ant colony algorithm. Through the simulation experiments of simulation examples and real examples, the traditional ant colony algorithm, tabu search improved ant colony algorithm and the knowledge-based ant colony algorithm proposed in this paper are compared and analyzed, and the effectiveness of the model and knowledge-based ant colony algorithm proposed in this paper is verified.