Optimization of drone base station locations and mobile charging drone routing for post-disaster communication

In the aftermath of a disaster, traditional communication systems often become inaccessible, creating significant challenges for rescue teams and affected individuals. This research aims to design an innovative communication system to bridge this gap, ensuring efficient information transfer and establishing reliable communication channels between rescue teams and affected people. The focus is on using drones as communication tools to address this challenge. The study explores the use of drones as data collection and transmission platforms in disaster-stricken areas. By collecting information from individuals, including text messages and location data from different platforms, drones can efficiently transmit vital data to the communication backhaul. An optimization model is formulated to decide on the 3D location of drone base stations while maximizing coverage and service quality. In addition, mobile power drones are also required to supply the power for deployed base stations and data transfer; the model also decides on the routing of multiple power drones. To solve the problem efficiently, a clustering-based matheuristic is developed to determine the locations of the base stations. We show the solution performance of the model and the effectiveness of our heuristic algorithm in a case study using data from Sultanbeyli province in Türkiye. The heuristic algorithm solves all the case study instances, which consist of 700 nodes, 75–105 stationary drones, and 6–8 mobile drones, in less than an hour. The results show that with 105 stationary and 8 mobile drones, we can cover 82% of the users. Furthermore, we demonstrate how this coverage can be increased to 95% by implementing certain adjustments. The findings offer insights into the potential of using drone base stations in post-disaster scenarios, thereby empowering disaster management agencies with enhanced communication capabilities for improved coordination and response in the face of disaster.

Authors

Publication Details

Journal
Computers & Operations Research
Published
2025-07-24
DOI
https://doi.org/10.1016/j.cor.2025.107206
Citations
5
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
24.97
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article

Optimization of drone base station locations and mobile charging drone routing for post-disaster communication

Farzad Avishan, İhsan Yanıkoğlu, Mehmet Berk Karasu, Melike Çap
5 citations
Computers & Operations Research
UAV Applications and Optimization
24.97
article

Optimization of drone base station locations and mobile charging drone routing for post-disaster communication

Farzad Avishan, İhsan Yanıkoğlu, Mehmet Berk Karasu, Melike Çap
article en
5 citations

Abstract

In the aftermath of a disaster, traditional communication systems often become inaccessible, creating significant challenges for rescue teams and affected individuals. This research aims to design an innovative communication system to bridge this gap, ensuring efficient information transfer and establishing reliable communication channels between rescue teams and affected people. The focus is on using drones as communication tools to address this challenge. The study explores the use of drones as data collection and transmission platforms in disaster-stricken areas. By collecting information from individuals, including text messages and location data from different platforms, drones can efficiently transmit vital data to the communication backhaul. An optimization model is formulated to decide on the 3D location of drone base stations while maximizing coverage and service quality. In addition, mobile power drones are also required to supply the power for deployed base stations and data transfer; the model also decides on the routing of multiple power drones. To solve the problem efficiently, a clustering-based matheuristic is developed to determine the locations of the base stations. We show the solution performance of the model and the effectiveness of our heuristic algorithm in a case study using data from Sultanbeyli province in Türkiye. The heuristic algorithm solves all the case study instances, which consist of 700 nodes, 75–105 stationary drones, and 6–8 mobile drones, in less than an hour. The results show that with 105 stationary and 8 mobile drones, we can cover 82% of the users. Furthermore, we demonstrate how this coverage can be increased to 95% by implementing certain adjustments. The findings offer insights into the potential of using drone base stations in post-disaster scenarios, thereby empowering disaster management agencies with enhanced communication capabilities for improved coordination and response in the face of disaster.

Computers & Operations ResearchVol. 184
Climate action
Openalex Percentile: Top 1%
UAV Applications and Optimization
24.97
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Optimization of drone base station locations and mobile charging drone routing for post-disaster communication — Farzad Avishan, İhsan Yanıkoğlu, et al. · Computers & Operations Research (2025) | TGRS Research Map | TGRS