Solving the location-routing problems Using Clustering Method

The distribution of products from depots to customers is a challenging problem in logistics management. The location of depots and the distribution of product from these depots to clients are two fundamental key of distribution system. The location-routing problem (LRP) combines the two levels of decisions: the strategic decision level to place warehouses, and the vehicle routes must be built at the tactical or operational levels. Given a fleet of identical vehicles and a set of customers with known demands. The problem consists of completing the depot to be opened, the customers and the vehicles to be selected to each depot, then determining vehicle routes. The objective is to minimize the costs to the performed routes. The proposed algorithm initially adopts K-means algorithm to execute the clustering analyses, which place the depots as the centroids of clusters and assigned the customers to each depot, then routed with Clarke and Wright saving method for every cluster. Further the routes are scheduled and optimized using two-opt algorithm. We give an implementation and an evaluation of the proposed method that we compare with the results of the best solution. The numerical results demonstrated the effectiveness of the new model.