Clustering-Based Heuristics for the Two-Echelon Vehicle Routing Problem

The Two-Echelon Vehicle Routing Problem (2E-VRP) is an extension of the classical VRP where the delivery from a single depot to customers is managed by routing and consolidating the freight through intermediate depots called satellites. We presented several meta-heuristics based on separating the first and second level routing problems and solving iteratively the two resulting routing subproblems, while adjusting the satellite workloads linking them. The two main meta-heuristics use a clustering and a multi-depot approach, respectively. We present experimental results comparing the meta-heuristics among them and with an exact method, as well as examining the impact of different customer and satellites spatial distributions on the performance of the methods and the cost of the distribution system. The experiments show that the clustering-based metaheuristics perform very well and that a two-echelon system may significantly reduce the cost of distribution.