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831. Stochastic Scheduling and Routing Decisions in Online Meal Delivery Platforms with Mixed Force
Invited abstract in session MA-52: Combinatorial optimization approaches for freight deliveries and home services, stream Combinatorial Optimization.
Monday, 8:30-10:00Room: 8003 (building: 202)
Authors (first author is the speaker)
| 1. | Claudia Archetti
|
| Università degli Studi di Brescia | |
| 2. | Laurent Alfandari
|
| ESSEC Business School | |
| 3. | Yanlu Zhao
|
| Durham University |
Abstract
This paper investigates stochastic scheduling and routing problems in the online meal delivery (OMD) service. The huge increase in meal delivery demand requires the service providers to construct a highly efficient logistics network to deal with a large-volume of time-sensitive and fluctuating fulfillment, often using inhouse and crowdsourced drivers to secure the ambitious service quality. We aim to address the problem of developping an effective scheduling and routing policy that can handle real-life situations. To this end, we first model the dynamic problem as a Markov Decision Process (MDP) and analyze the structural properties of the optimal policy. Then we propose four integrated approaches to solve the operational level scheduling and routing problem. In addition, we provide a continuous approximation formula to estimate the bounds of required fleet size for the inhouse drivers.
Numerical experiments based on a real dataset show the effectiveness of the proposed solution approaches. We also obtain several managerial insights that can help decision makers in solving similar resource allocation problems in real-time.
Keywords
- Combinatorial Optimization
- Vehicle Routing
- E-Commerce
Status: accepted
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