Route Optimization Of Tobacco Distribution Based On Clustering-Tabu Search Algorithm

As the terminal link of tobacco logistics system, the logistics center of a prefecture level tobacco company is in charge of cigarette distribution according to orders. How the delivery route works has a great influence on the logistics cost and distribution efficiency. A good route planning can help realize enterprise’s economic benefit, improve customer satisfaction and enhance the core competitiveness of enterprises.By analyzing both the current researches on route optimization of cigarette distribution and the current status of cigarette distribution in transfer station B of tobacco company A, the study uses the method of combining mathematical modeling and Two-phase heuristic in order to reduce the distribution cost, improve the efficiency of distribution. The core concept is to solve the problem in three stages. First of all, we divide the delivery region into several parts with K-means Algorithm. Second, we optimize the distribution routes in single delivery region with Tabu Search Algorithm. Finally, as there is residual loading capacity in some routes, we adjust the delivery regions by the results we get in the second step.This thesis selects transfer station B of tobacco company A for the study and provides a route optimization. As a route optimization of tobacco distribution has its special industrial characteristics, it has a certain reference value for logistics distribution of some companies with the same Distribution characteristics.