The problem of dispatching shuttles to serve trip requests can be mathematically formulated as a dial-a-ride problem (DARP). With on-demand mobility services gaining more popularity in recent years, the real-time application of DARP is attracting ever more interest. However, the fact that size of DARP grows exponentially with number of requests renders the current solution methodologies inadequate for online applications. In order to tackle this issue, we propose a general framework that shifts much of the computational burden of the optimization problems that need to be solved into an offline setting, thereby addressing on-demand requests with fast and high-quality solutions in real time. Furthermore, in order to improve the utilization rate of vehicles, we seek to dispatch our shuttle proactively, and not wait for the demand to be realized first. Using various numerical experiments, we demonstrate the benefits of the proposed method. Furthermore, we present a sensitivity analysis to show the performance of our methodology under different parameter settings.

Amir is a Ph.D. candidate in the Department of Civil and Environmental Engineering at University of Michigan, Ann Arbor. He is working under the supervision of Dr. Neda Masoud.