Abstract:

This paper presents a new mixed integer problem (MIP) formulation for the Charging Location and Electric Vehicle Scheduling Problem (CLEVSP). The CLEVSP aims at minimizing the investment costs for charging infrastructure and electric buses as well as the operational costs resulting from the vehicle schedule of an electric bus system applying opportunity charging. Leveraging the assumption of a homogeneous vehicle fleet, the presented MIP is based on two-index decision variables for vehicle scheduling. The Gurobi optimization software is used to find near-optimal solutions for small and medium-sized cities' CLEVSP problems. The model is competitive with state-of-the-art methods even for large-scale problems with thousands of service trips. The model's convergence behavior depends on the problem's difficulty, which is influenced by the number of service trips and the available battery capacity of electric buses.