Location planning techniques for Internet provider service unmanned aerial vehicles during crisis
Kassem Danach, Hassan Harb, Ameer Sardar Kwekha Rashid, Mutaz Al-Tarawneh, Wael Hosny Fouad Aly
Abstract
In situations where conventional communication networks are compromised, deploying Internet Provider Service Unmanned Aerial Vehicles (UAVs) becomes essential for re-establishing connectivity. This study presents a hyperheuristic framework aimed at optimizing the positioning and management of these UAVs, with a focus on enhancing coverage, reducing latency, and managing operational costs. The framework employs a dynamic selection of multiple low-level heuristics, guided by real-time problem conditions and a Monte Carlo-based decision process. The performance of this approach was evaluated through simulations across 40 different scenarios, encompassing urban, suburban, rural, and mixed environments. The results show that the hyperheuristic method consistently delivered high coverage, achieving 94.6% in urban settings, 88.3% in suburban areas, 82.0% in rural regions, and 85.0% in mixed conditions. These outcomes highlight the flexibility and effectiveness of the hyperheuristic approach in adapting to various crisis scenarios. This research not only provides practical insights for UAV deployment but also advances the field of combinatorial optimization through innovative hyperheuristic techniques. • A hyper-heuristic framework for optimizing and managing UAVs is proposed. • The framework focuses on enhancing coverage, latency, and operational costs. • The framework employs a dynamic selection of multiple low-level heuristics. • It is guided by real-time problem conditions and a Monte Carlo decision process.