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1161. The Stochastic Location-Routing Problem with Truck-Drone Tandem for Humanitarian Aid Delivery
Invited abstract in session TA-21: Humanitarian aid provision and disposal, stream OR in Humanitarian Operations (HOpe).
Tuesday, 8:30-10:00Room: 49 (building: 116)
Authors (first author is the speaker)
1. | Hannan Tureci Isik
|
Management, University of Bath | |
2. | Melih Celik
|
School of Management, University of Bath | |
3. | Ece Sanci
|
Amazon |
Abstract
Timely response is crucial in humanitarian logistics to reduce suffering and loss. Network disruptions after a disaster, or due to unreliable networks, can cause prolonged travel times or isolate locations. These uncertainties necessitate a systematic approach to anticipate challenges in humanitarian logistics and ensure timely aid delivery. We propose a novel network design problem that strategically locates depots to enable efficient post-disaster deliveries. We incorporate the post-disaster uncertainties through stochastic travel times on the road network and formulate the resulting stochastic location-routing problem as a two-stage stochastic program. We explore the integration of drones with ground vehicles to overcome the network inaccessibility and long travel times on the road network to improve response times. We focus on independent truck-drone deliveries from depots to transport lightweight aid bundles, such as medical supply kits, weather protection items, or communication tools. We develop a tailored heuristic based on variable neighbourhood search and compare its performance with CPLEX in small instances. We implement the heuristic in a case study of the Van Earthquake 2011, Türkiye. Through this implementation, we evaluate the value of the stochastic modelling approach and the tandem delivery model and perform sensitivity analysis. Our results show that the use of drones can significantly enhance delivery times by more than 50% in our case study.
Keywords
- Disaster and Crisis Management
- Humanitarian Applications
- Stochastic Models
Status: accepted
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