Design and optimization of logistics distribution route based on improved ant colony algorithm

Abstract

To improve the effect of logistics distribution path optimization design, this paper combines the improved ant colony algorithm to study the logistics distribution path design and optimization. The key point of the fusion of genetic algorithm and improved ant colony algorithm is that the path optimal solution is transformed into the initial distribution of pheromone, and the transformed model rules affect the final algorithm effect. In addition, the mutation operator forms new individuals by changing the gene values of certain positions on the individual chromosomes to expand the search space to areas that may not be close to the current population, so that the genetic algorithm has local random search capabilities and accelerates the convergence to the optimal solution. Through the analysis, it can be known that the logistics distribution route optimization design and optimization method based on the improved ant colony algorithm proposed in this paper has good results.