A Hybrid Optimization Framework for Dynamic Drone Networks: Integrating Genetic Algorithms with Reinforcement Learning

The growing use of unmanned aerial vehicles (UAVs) in diverse fields such as disaster recovery, rural regions, and smart cities necessitates effective dynamic drone network establishment techniques. Conventional optimization techniques like genetic algorithms (GAs) and particle swarm optimization (P...

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出版年:	Applied Sciences
主要な著者:	Mustafa Ulaş, Anıl Sezgin, Aytuğ Boyacı
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2025-05-01
主題:	drone networks unmanned aerial vehicles genetic algorithms reinforcement learning Q-learning multi-objective optimization
オンライン･アクセス:	https://www.mdpi.com/2076-3417/15/9/5176