Vehicle Routing Optimization of Tobacco Distribution Using Fuzzy C-Means Clustering and Ant Colony Algorithm

Abstract

In order to further optimize its vehicle routing and improve the distribution efficiency, the mathematical model of tobacco distribution with multi-vehicle is established. A novel optimization distribution strategy is proposed, which combines Fuzzy C-Means Clustering (FCM) with Ant Colony Algorithm (ACA). Firstly, the local distribution region of different distribution vehicles is obtained by FCM algorithm. Then, optimize the path of different distribution regions based on ACA. Finally, taking a distribution center in Zhengzhou city as an example, comparison simulation experiments were carried on compared to Simulated Annealing algorithm. The results show that, proposed optimization strategy shortens the distance of tobacco distribution vehicle, optimize the distribution route, and then reduce the distribution cost.