Research on Agricultural Machine Scheduling in Hilly Areas Based on Improved Non-Dominated Sorting Genetic Algorithm-III

Abstract

To address the problem of inefficient continuous multi-task scheduling operations, a scheduling model was established with the optimization objective of minimum total scheduling time to solve the problem of agricultural machinery continuous performing multiple tasks in agricultural production in hilly areas. An Improved Non-dominated Sorting Genetic Algorithm-III (Improved NSGA-III) was proposed to solve the agricultural machinery scheduling problem. The algorithm employed a two-stage coding mechanism to ensure the uniform distribution of the population and reduce the search solution space. The selection of paternal individuals is based on crowding degree, enabling individuals with better genes to participate in evolution. The domain search strategy of partial solution was introduced to improve the global search ability of the algorithm. The performance of the Improved NSGA-III algorithm and the other three algorithms was compared using farmland data from the experimental area. Results showed that the Improved NSGA-III algorithm outperforms the other three algorithms in terms of minimum total scheduling time, with reductions of 13.89%, 43.81% and 57.19%, respectively, verifying the effectiveness and reliability of the algorithm.