Abstract
Carsharing systems have attracted considerable market interest owing to their positive impact on resolving social and environmental pollution problems such as traffic congestion, lack of parking spaces, and greenhouse gas emissions. However, one-way carsharing systems often struggle with vehicle imbalance issues, which can affect customer satisfaction. To address this, a one-way electric carsharing model was designed to maximize operator revenue by introducing customer space flexibility. A mixed integer nonlinear program was formulated to optimize consumer flexibility, relocation, and employee-hiring decisions. The variation in the average vehicle charge at each station was captured using the state of change (SOC) model. Real data from the Evo carsharing company in Vancouver, Canada, were used to conduct numerical tests, verifying the effectiveness of the rolling horizon method in producing high-quality solutions. The results indicate that customer space flexibility can enhance the operational efficiency of carsharing systems without increasing the number of vehicles or parking spaces. This approach can also boost total system revenue and customer satisfaction, with departure space flexibility showing a significantly greater impact than arrival space flexibility.