Logistics Distribution Path Planning Based On Genetic Algorithm

Abstract

The logistics distribution path planning is of great significance for improving logistics distribution efficiency and saving the cost of distribution. Traditional logistics distribution path planning is usually a model that a single supplier serves several demands, which regards the minimum total distance distribution as the optimization goal and aims to pursue the optimal distribution route. But the logistics distribution model in this paper is that several suppliers serve several demands, then transforms into the classical TSP to solve optimization problems and mathematical model is established. Based on the mathematical model, the improved genetic algorithm is supported to use integer permutation encoding and adopt the optimal individual reserve strategy and roulette method on the individual selection. Finally, experiments have been carried out to calculate in this way, according to the calculation results, it shows that using the genetic algorithm to solve optimize logistics distribution route can obtain effectively the optimal solution or approximate optimal solution about this problem.