A hybrid variable neighborhood search approach for the multi-depot green vehicle routing problem

Abstract

The Multi-Depot Green Vehicle Routing Problem (MDGVRP) is an extension of the well-known Green Vehicle Routing Problem (GVRP) where a fleet of alternative fuel-powered vehicles (AFVs) are used to serve the customers. GVRP consists of determining AFV tours such that the total distance travelled is minimum. The AFVs depart from the depot, serve a set of customers, and complete their tours at the depot without exceeding their driving range and the maximum tour duration. AFVs may refuel en-route at public refueling stations. In MDGVRP, the AFVs are dispatched from different depot locations and may refuel during the day at any depot or refueling station. We formulate MDGVRP as a mixed integer linear programming model and develop a hybrid General Variable Neighborhood Search and Tabu Search approach by proposing new problem-specific neighborhood structures to solve the problem effectively. We assess the performance of our method using the GVRP dataset from the literature. Our results show that the proposed method can provide high quality solutions in short computation times. Then, we extend these instances to the multi-depot case and compare our solutions for small-size instances with the optimal solutions. We also report our results for large-size problems and investigate the trade-offs associated with operating multiple depots and adopting different refueling policies to provide further insights for both academicians and practitioners.