Selective Multi-Grade Charging Scheduling and Rebalancing for One-Way Car-Sharing Systems

This paper investigates the rebalancing and charging scheduling problem of one-way car-sharing systems. Vehicles can be charged either at the stations within the system or at the public charging stations. A framework for selective multi-grade charging scheduling and fleet rebalancing is proposed. To this end, vehicles and customers are classified into different grades for scheduling and matching, according to their state of charge and travel distance, respectively. The number of grades is involved as a decision variable in the combinatorial optimization problem, with the objective of minimizing the maximum response time and the operating cost for both rebalancing and charging. A lower bound optimal solution of the problem is given analytically based on the Lagrangian analysis and the Karush-Kuhn-Tucker (KKT) condition, yielding a joint optimization algorithm that can ensure the quality of service and balanced demand-supply in the system. Simulation results show that the method is effective in reducing system response time, improving vehicle utilization and reducing reliance on vehicle charging.