149. Uncapacitated Facility Location Problem for Drone-Based Intermodal Distribution Networks
Invited abstract in session FA-10: Network Design, stream Supply Chain Management and Production.
Friday, 8:45-10:15Room: H16
Authors (first author is the speaker)
| 1. | Asrat Mekonnen Gobachew
|
| Logistics and Supply Chain Management, Fachhochschule Südwestfalen | |
| 2. | Stefan Lier
|
| FH Südwestfalen |
Abstract
The rise of drone-based logistics is transforming last-mile delivery, necessitating new facility location models that account for unique operational constraints of drones. This research proposes a hybrid approach to identify potential locations for micro-hubs and intermediate hubs within an intermodal drone delivery network. The network consists of a central warehouse that supplies micro-hubs using trucks, while drones handle last-mile deliveries to customers. To address the challenge of continuous facility location without predefined candidate sites, DBSCAN clustering is integrated with an uncapacitated facility location model. Clustering serves as a preprocessing step to identify initial micro-hub candidate locations based on customer distribution, reducing computational complexity. These candidate locations are then refined through optimization that assigns customers to the nearest feasible facility within drone range, applying penalties for unassigned locations. For customers beyond drone range, intermediate hubs are introduced at regular intervals to ensure service coverage. Infeasible facility sites, such as those located in water bodies or restricted zones, are relocated to nearby viable alternatives. A case study utilizing real-world data from two logistics providers demonstrates full customer coverage and validates the effectiveness of the proposed model. The framework supports strategic planning for scalable, drone-integrated logistics networks. Future work will focus on incorporating capacity constraints, dynamic routing, and multi-objective optimization to enhance sustainability and operational realism.
Keywords
- Logistics
- Location
- Network Design
Status: accepted
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