Management of Dynamic Vehicle Allocation for Carsharing Systems

Abstract

Carsharing offers innovative mobility solutions and has been gaining popularity around the world as an environmentally sustainable, socially responsible, and economically feasible form of mobility. Carsharing allows members to benefit from private vehicle use without the costs and responsibilities of ownership and provides individuals with access to a fleet of shared-use vehicles in a network of locations on a short-term, as-needed basis. This paper seeks to develop a stochastic optimization framework to address the dynamic vehicle allocation problem for carsharing systems, in which the service operator needs to manage and determine the optimal vehicle allocation in both time and space to maximize profits. A multistage stochastic linear programming model with recourse, which can account for system uncertainties such as car-sharing demand variation, is formulated and solved. Numerical results are discussed and computational insights are presented on the basis of a seven-stage experimental network pilot study.