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2522. A time-space network model for a truck and drones delivery system
Invited abstract in session TD-26: Routing for hybrid fleets of vehicles, stream Combinatorial Optimization.
Tuesday, 14:30-16:00Room: 012 (building: 208)
Authors (first author is the speaker)
| 1. | Dell'Olmo Paolo
|
| Dipartimento di Statistica, Probabilità, Statistiche applicate, University of Rome La Sapienza | |
| 2. | Lavinia Amorosi
|
| Statistical Sciences, Sapienza | |
| 3. | Justo Puerto
|
| Estadistica e I.O., Universidad de Sevilla | |
| 4. | Carlos Valverde
|
| University of Seville |
Abstract
We present a bi-objective multi-period mixed integer linear programming formulation based on a time-space network for a delivery problem with an automated mothership and a fleet of drones. The proposed formulation integrates not only the routing and the scheduling problems underlying the delivery, but also the charging cycles of drone batteries with the movements of the mothership. The two objective functions are the minimization of the mothership and UAVs energy consumption and the maximization of the number of served customers. Indeed, it is assumed that not all customers can be served within the time horizon under consideration. Experimental results on a testbed of artificial instances will be presented.
Keywords
- Combinatorial Optimization
- Programming, Multi-Objective
- Scheduling
Status: accepted
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