Optimization of personalized price discounting scheme for one-way station-based carsharing systems

Abstract

As a promising pattern of shared mobility, one-way carsharing systems provide users with flexible car-rental services and have enjoyed rapid development in the past few years. Almost all previous relevant optimization studies assume that the objective of the pricing or discounting scheme is to balance the fleet from the standpoint of the carsharing companies. However, the users’ preferences for various levels of service have not been explored sufficiently. This paper introduces a carsharing personalized price discounting scheme (CSPPDS) problem for one-way reservation-based11It is assumed that users make reservations for their trips one day ahead of set-off in this work. services, considering user acceptance of the discounted price and various levels of service that the system provides to the users. To maximize the system’s profit, the presented CSPPDS problem decides the discounting scheme and whether to accept the requests. Meanwhile, the actual requests travel plans that can be different from the users’ original travel requests in pick-up locations and start times are optimized. A real-world case study based on a one-way carsharing system in Beijing is conducted to demonstrate the applicability of the presented model.