A Multiregional Agricultural Machinery Scheduling Method Based on Hybrid Particle Swarm Optimization Algorithm

Huang Huang (), Xinwei Cuan, Zhuo Chen, Lina Zhang and Hao Chen
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Huang Huang: College of Engineering, Huazhong Agricultural University, Wuhan 430070, China
Xinwei Cuan: College of Engineering, Huazhong Agricultural University, Wuhan 430070, China
Zhuo Chen: College of Engineering, Huazhong Agricultural University, Wuhan 430070, China
Lina Zhang: Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing 100083, China
Hao Chen: College of Engineering, Huazhong Agricultural University, Wuhan 430070, China

Agriculture, 2023, vol. 13, issue 5, 1-18

Abstract: The reasonable scheduling of agricultural machinery can avoid their purposeless flow during the operational service and reduce the scheduling cost of agricultural machinery service centers. In this research, a multiregional agricultural machinery scheduling model with a time window was established considering the timeliness of agricultural machinery operation. This model was divided into two stages: In the first stage, regions were divided through the Voronoi diagram, and farmlands were distributed to intraregional service centers. In the second stage, the model was solved using the hybrid particle swarm optimization (HPSO). The algorithm improves the performance of the algorithm by introducing a crossover, mutation, and particle elimination mechanism, and by using a linear differential to reduce the inertia weight and trigonometric function learning factor. Next, the accuracy and effectiveness of the algorithm are verified by different experimental samples. The results show that the algorithm can effectively reduce the scheduling cost, and has the advantages of strong global optimization ability, high stability, and fast convergence speed. Subsequent algorithm comparison proves that HPSO has better performance in different situations, can effectively solve the scheduling problem, and provides a reasonable scheduling scheme for multiarea and multifarmland operations.

Keywords: scheduling model; time window; two-stage algorithm; Voronoi diagram; particle swarm arithmetic (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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