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1869. A Vehicle Routing Problem with Divisible Deliveries and Pickups under Uncertainty
Invited abstract in session MC-35: Urban Logistics and sustainable TRAnsportation: OPtimization under uncertainTY and MAchine Learning, stream Stochastic, Robust and Distributionally Robust Optimization.
Monday, 12:30-14:00Room: 44 (building: 303A)
Authors (first author is the speaker)
| 1. | Francesca Vocaturo
|
| Department of Economics, Statistics and Finance, University of Calabria | |
| 2. | Alessandro Gobbi
|
| Dipartimento di Ingegneria dell’Informazione, Università degli Studi di Brescia | |
| 3. | Daniele Manerba
|
| Dept. of Information Engineering, Università degli Studi di Brescia |
Abstract
Most e-commerce companies design combined delivery-pickup logistics systems, where the collection of unsatisfactory items is ensured along with the traditional distribution of products to customers. In this context, a successful option is to solve a Vehicle Routing Problem with Divisible Deliveries and Pickups (VRPDDP) where each customer requiring both a pickup and a delivery service may be served, if beneficial, in two separate visits. In the version of the problem analyzed in our study, there are mandatory delivery and pickup demands that must be fulfilled by a fleet of homogeneous vehicles. In addition, it is needed to ensure that a percentage of optional pickups is served. Optional pickup demands are affected by uncertainty and random variables are used for their representation. In this sense, we refer to our problem as stochastic VRPDDP and model it as a two-stage stochastic program with recourse. More specifically, a set of routes is designed at the first stage. At the second stage, when uncertainty is revealed, it may be impossible to implement the solution as planned at the first stage. Then, two different recourse actions are carried out. The computational experiments confirm the usefulness of using stochastic programming in realistic setting.
Keywords
- Vehicle Routing
- Stochastic Optimization
- Reverse Logistics / Remanufacturing
Status: accepted
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