Comparative Analysis of Genetic and Greedy Algorithm for Optimal Drone Flight Route Planning in Agriculture

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dc.contributor.authorÖnler, Eray
dc.date.accessioned2024-10-29T17:55:19Z
dc.date.available2024-10-29T17:55:19Z
dc.date.issued2024
dc.departmentTekirdağ Namık Kemal Üniversitesi
dc.description.abstractIn this study, the performance of the Genetic Algorithm (GA) in optimizing the agricultural drone flight route was compared with the Greedy Algorithm, revealing that GA produce routes that are, on average, 17.44 % more efficient. This efficiency, measured over 500 generations in a static field model, suggests substantial potential for saving resources and time in agricultural operations. Despite the effectiveness of the GA, its computational intensity limits real-time field applications, but offers advantages in offline route planning for pre-mapped areas. A t-test between flight lengths created by the algorithms highlighted a significant difference, with a p-value of approximately 7.18×10?9, indicating the GA's superior performance. Future research should aim to bridge the gap between the simplified binary field model used in simulations and the complexities of real-world agricultural landscapes to improve the practical deployment of GAs in drone route optimization.
dc.identifier.doi10.7161/omuanajas.1394616
dc.identifier.endpage142
dc.identifier.issn1308-8750
dc.identifier.issn1308-8769
dc.identifier.issue1en_US
dc.identifier.startpage129
dc.identifier.trdizinid1226721
dc.identifier.urihttps://doi.org/10.7161/omuanajas.1394616
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/1226721
dc.identifier.urihttps://hdl.handle.net/20.500.11776/13960
dc.identifier.volume39
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofAnadolu Tarım Bilimleri Dergisi
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectAgricultural drone
dc.subjectdrone route optimization
dc.subjectoffline route planning
dc.titleComparative Analysis of Genetic and Greedy Algorithm for Optimal Drone Flight Route Planning in Agriculture
dc.typeArticle

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