1298. A rolling horizon approach to coordinating ride-hailing platforms and public transit systems
Invited abstract in session WB-30: Shared Mobility Optimization III, stream Shared Mobility Optimization.
Wednesday, 10:30-12:00Room: Maurice Keyworth 1.05
Authors (first author is the speaker)
| 1. | Thomas De Munck
|
| Center for Operations Research and Econometrics, UCLouvain | |
| 2. | Jean-Sébastien Tancrez
|
| CORE - Louvain School of Management, Université catholique de Louvain | |
| 3. | Jorge Vera Andreo
|
| Department of Industrial and Systems Engineering, Pontificia Universidad Católica de Chile |
Abstract
This work considers the online dispatching problem of a ride-hailing platform (e.g., Uber) that coordinates with a public transit system. Customers are impatient and make requests randomly over time. For each request, the platform must decide (i) whether to provide door-to-door, first-mile, or last-mile service and (ii) which drivers to dispatch to the resulting service. To address this problem, we propose a rolling horizon approach based on stochastic optimization. The approach includes a route selection procedure, and a Benders decomposition to improve its applicability in realistic settings. In numerical experiments, we first demonstrate the effectiveness of our approach in comparison with rolling-horizon approaches based on deterministic optimization. Then, we provide managerial insights into the benefits of coordinating ride-hailing services with public transit by analyzing various supply-demand patterns and transit network configurations.
Keywords
- Transportation
- E-Commerce
- Programming, Stochastic
Status: accepted
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