Optimization of Logistics Distribution Route Based on Improved Genetic Algorithm

Through research, we found that using the TSP (Traveling Salesman Problem) algorithm to optimize logistics distribution routes can significantly reduce transportation costs, thereby achieving better transportation results. Therefore, we conceived a new genetic algorithm to implement different transportation strategies according to different needs, such as sequences, minimum cost trees, random point lengths, etc., to achieve better transportation results. After in-depth simulation and analysis, we found that the new genetic algorithm performs superior in searching and predicting in complex environments, and its convergence speed is much faster. Therefore, it can be an efficient logistics distribution route optimization technique.