Combined passenger and parcel transportation using a mixed fleet of electric and gasoline vehicles

This study deals with a variant of the vehicle routing problem that aims to design the optimal routes for a mixed fleet of taxis that simultaneously services a given set of passenger and parcel requests. The fleet is composed of electric vehicles and gasoline vehicles. The problem is called combined passenger and parcel transportation problem with a mixed fleet (CPPT-MF). We construct a time-expanded network which is used to model the movements of passengers, parcels and vehicles in space and time. A mixed-integer linear programming model of the problem is developed on the basis of the time-expanded network. A network partitioning-based math-heuristic is proposed to efficiently solve large-scale instances of the problem. The model and the heuristic are evaluated using a set of real-world instances from a taxi company and a set of randomly generated instances. The computational results show that the proposed approach is effective and efficient for solving the CPPT-MF and could facilitate taxi companies with heterogeneous fleets for deciding the routes to simultaneously service passenger and parcel requests.