Joint optimization of infrastructure deployment and fleet operations for an electric carsharing system by considering multi-type vehicles

Abstract

Electric carsharing (ECS) is considered an effective option to alleviate resource and environmental issues in urban transportation. In this study, we develop a mixed-integer optimization model to jointly optimize infrastructure deployment (station construction and fleet configuration) and fleet operations (vehicle assignment and charging strategy) for the ECS to maximize profits. The model further considers users’ diversified demands and incorporates multi-type electric vehicles into the problem formulation. The user-based assignment and on-demand charging strategy are also integrated into the model to improve the operational efficiency. A specialized logic-based Benders decomposition algorithm is customized to effectively solve the model. A real-life case in Lanzhou, China, is presented to demonstrate the proposed methods. Results indicate that the model has better performance and can increase profits by 20% compared with conventional methods, as hybrid fleet deployment is more energy-saving and can save up to 10% of the energy costs compared with a homogeneous fleet.