A New Cluster-Based Approach for the Vehicle Routing Problem with Time Windows

Modern logistics receives increasing attention for planning and scheduling operations of transport systems that have to be resource efficient and environmentally sustainable. A well known model for solving routing problems with time windows and vehicles is the Vehicle Routing Problem with Time Windows (VRPTW). This paper proposes a VRPTW algorithm based on cluster first, route second methods. In particular, first, by using a graph partitioning Integer Linear Programming problem, the algorithm generates a number of clusters equal to the number of available vehicles. Then, each vehicle solves a Travelling Salesman Problem with Time Windows to compute its route in the assigned cluster. Numerous benchmark problems featuring different sizes, random customer locations and time window distributions are solved and compared with the optimal solution. Moreover, a real case study shows the efficiency of the solution method..