UAV routing by simulation-based optimization approaches for forest fire risk mitigation

Omer Ozkan () and Sezgin Kilic ()
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Omer Ozkan: Turkish Air Force Academy, National Defence University
Sezgin Kilic: Air NCO Vocational HE School, National Defence University

Annals of Operations Research, 2023, vol. 320, issue 2, No 16, 937-973

Abstract: Abstract The magnitude of the recent forest fires, the time required to extinguish them, and the damage they caused have attracted the attention of all humanity. If the current trend continues, it will cause great irreversible losses. There is a great need for scientific studies to prevent or reduce the damages of these fires. In this context, this paper proposes algorithms and mathematical models for generating the routes of unmanned aerial vehicles to detect forest fires that may occur especially in regions far from residential areas. A novel heuristic dispatching rule and a simulation-based optimization algorithm are proposed. The striking features of the proposed algorithms are that the routes are created with a focus on minimizing the fire probabilities. The uncertainties and dynamics of real-life are also considered. Various scenarios have experimented on a realistic case. Experimental results and findings are promising.

Keywords: Simulation-optimization; UAV routing; Forest fire; Fire detection (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10479-021-04393-6

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