Automation in Agriculture: A Case Study of Route Planning Using an Evolutionary Lovebird Algorithm

Abstract

A recent trend in the agricultural sector is the integration of computers to support automation in the operation of small and large-scale farms. The utilization of computers for decision making is critical for farmers wanting to lower their operative costs and control their machines. The focus of this paper is on the optimization of route planning for agricultural machines that are applying fertilizer on fields. The output of this research is expected to support automation in agriculture by helping farmers to choose the most efficient route for their machines. This study formalizes the decisional problem with a mathematical formula and presents a new improved algorithm, Evolutionary Lovebird Algorithm, to solve the problem. The experimental results show that the proposed algorithm can save 8.45% of the non-working distance compared to other algorithms. Moreover, on average, the running time of the proposed algorithm is only one-third of other algorithms, thereby making the Evolutionary Lovebird Algorithm three times more efficient than other algorithms.