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

Authors : Eray Önler

Pages : 129-142

Doi:10.7161/omuanajas.1394616

View : 65 | Download : 72

Publication Date : 2024-02-29

Article Type : Research Paper

Abstract :In 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.
Keywords : Dron rota optimizasyonu, tarımsal dron, çevrimdışı rota planlama