VRP algorithms for decision support systems to evaluate collaborative urban freight transport systems

This paper proposes a comparison between genetic and semi-greedy algorithms for a collaborative VRP in city logistics. In order to compare the performance of both algorithms on real-size test cases, we develop a cluster-first route second algorithm. The clustering phase is made by a seep algorithm, which defines the number of used vehicles and assigns a set of customers to it. Then, for each vehicle, we build a min-cost route by two methods. The first is a semi-greedy algorithm. The second is a genetic algorithm. We test both approaches on real-size instances Computational results are presented and discussed.