Optimizing one-way electric carsharing operations using real-time information

One-way systems provide flexibility for their users. However, operators prefer to implement round-trip systems since they are easy and less costly to implement. In one-way carsharing systems, users are usually allowed to reserve an available vehicle shortly (not more than 30 minutes) before the desirable pick-up time. Providing the flexibility of early reservations in one-way systems can increase the demand by attracting more customers and can lead to a better utilization of the available resources. In this work, we combine different types of demand (with different levels of information) for a one-way non-floating electric carsharing system, and develop an optimization-simulation framework for optimizing its operation. We assume that the users can provide in advance information regarding pick-up and drop-off locations and times and they will update this information as necessary before they return the car. We incorporate the available information into a model aiming to optimize operational decisions regarding vehicle and personnel relocation. We compare the performance of the system with different levels of available information using the data of the carsharing system in Nice, France