Research on cold chain logistics distribution path optimization based on improved ant colony algorithm

In real life, how to quickly and accurately plan the optimal path for cold chain logistics distribution in the complex traffic environment is one of the key issues in the cold chain logistics distribution vehicle operation system. Based on the classic ant colony algorithm, combined with the particularity of cold chain logistics distribution, considering the factors such as transportation cost, maximum vehicle load, distribution distance and traffic capacity of each road section, an optimal model of cold chain logistics distribution path planning based on the improved ant colony algorithm is established. On the basis of the classical ant colony algorithm, a cold chain logistics distribution path planning optimization model based on the improved ant colony algorithm is established. The model takes into account the special characteristics of cold chain logistics distribution in terms of transportation cost, maximum vehicle weight, distribution distance and access road capacity. In this paper, numerical simulation is performed with the help of MATLAB software to test the scientificity and rationality of the algorithm. The conclusion shows that the improved ant colony algorithm can get the distribution path suitable for the attributes of cold chain logistics and reduce the total transportation costs. The problem of selecting the optimal path of cold chain logistics distribution vehicles can be reasonably solved. This is conducive to improving the distribution efficiency of cold chain logistics and has strong practicality.