Optimization of UAV Positioning: A Comparative Study of PSO, Greedy, and Hybrid Algorithms for Energy Efficiency and Handover Cost

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Özdemir H. İ., Namdar M., Başgümüş A., Saraoğlu H. M.

IEEE International Conference on Electrical and Electronics Engineering 2025, Bursa, Turkey, 27 - 29 November 2025, no.130, pp.1-5, (Full Text)

• Publication Type: Conference Paper / Full Text
• City: Bursa
• Country: Turkey
• Page Numbers: pp.1-5
• Kütahya Health Sciences University Affiliated: Yes

Abstract

Unmanned Aerial Vehicles (UAVs) are increasingly utilized
in swarms, providing effective solutions to a wide range of
challenges. This study focused on positioning swarm UAVs
as base stations, particularly in disaster scenarios. The po-
sitioning process was optimized with respect to energy ef-
ficiency and handover cost. Accordingly, an optimization
problem was formulated to minimize both the distance to
the mission center and the handover cost. To solve this prob-
lem, the performance of several algorithms was analyzed,
including Particle Swarm Optimization (PSO), Firefly Al-
gorithm (FA), Bat Algorithm (BA), Artificial Bee Colony
(ABC) Algorithm, Greedy Algorithm (GA), and a hybrid
PSO-Greedy Algorithm approach. The findings revealed
that the hybrid algorithm outperformed all other methods.
In particular, the hybrid PSO-Greedy Algorithm achieved
the best energy performance, with a value of 6.29.