1321. Online vehicle routing with dynamic demand management
Invited abstract in session MB-27: Vehicle Routing under Uncertainty , stream Stochastic and Robust optimization.
Monday, 10:30-12:00Room: Maurice Keyworth G.02
Authors (first author is the speaker)
| 1. | Yossiri Adulyasak
|
| Gestion des Opérations et de la Logistique, HEC Montréal | |
| 2. | Linchuan Wei
|
| HEC Montreal | |
| 3. | Emma Frejinger
|
| Université de Montréal |
Abstract
Motivated by a real-world application, we consider the integrated vehicle routing and dynamic booking management problem under uncertain time windows. In this context, the logistics provider offers each customer personalized time window options and accepts their delivery requests in an online fashion. The challenge of this problem lies in the trade-off between flexibility and operational costs. On the one hand, providing more options increases customer satisfaction and the likelihood of receiving a request. On the other hand, offering a large number of time window options to customers may result in inefficient vehicle routes and schedules, as too many customers may select high-demand time slots. To solve this problem, we incorporate customer choice models to capture customers' preferences for time windows in the vehicle routing problem. The primary decisions include the personalized time window options made available to each customer, the acceptance of booking requests, and vehicle dispatching plans, which are all made in an online and dynamic fashion. The problem is modeled using the dynamic programming framework, which is solved by a linear programming approximation and a column generation approach. We demonstrate the efficiency and effectiveness of the solutions using the data from our industrial partner.
Keywords
- Programming, Stochastic
- Vehicle Routing
- Programming, Dynamic
Status: accepted
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