Construction of Orchard Agricultural Machinery Dispatching Model Based on Improved Beetle Optimization Algorithm

In order to enhance orchard agricultural efficiency and lower fruit production expenses, we propose a BL-DBO (Beetle Optimization Algorithm introducing Bernoulli mapping and Lévy flights) to solve the agricultural machinery dispatching model within the orchard area. First, we analyze the agricultural machinery dispatching problem in the orchard area and establish its mathematical model with the objective of minimizing dispatching costs as a constraint. To tackle the problems of uneven individual position distribution and the risk of becoming stuck in local optimal solutions in the traditional DBO algorithm, we introduce Bernoulli mapping during the initialization phase of the DBO. This method ensures a uniform distribution of the initialized population. Furthermore, during the iterative process of the algorithm, we incorporated the Lévy flight approach into the positional update equations for beetles involved in breeding, foraging, and theft activities within the DBO. This helps the beetles escape from local optimal solutions. Finally, we conduct experiments based on location information of Shunping Shunnong Orchard and fruit trees in Shijiazhuang. The results indicate that, compared to dispatching using human experience and the traditional DBO algorithm, the dispatching results generated by the BL-DBO not only reduce the number of agricultural machinery purchases but also decrease the energy loss from non-working distances of the machinery, effectively saving fruit production costs.

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Publication Details

Journal
Agronomy
Published
2025-01-27
DOI
https://doi.org/10.3390/agronomy15020323
Citations
1
Primary Topic
Advanced Algorithms and Applications
Type
article
Field-Weighted Citation Impact
1.21
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article

Construction of Orchard Agricultural Machinery Dispatching Model Based on Improved Beetle Optimization Algorithm

Hongjie Liu, Pengfei Wang, Lixing Liu, Jianping Li et al.
1 citations
Agronomy
Advanced Algorithms and Applications
1.21
article

Construction of Orchard Agricultural Machinery Dispatching Model Based on Improved Beetle Optimization Algorithm

Hongjie Liu, Pengfei Wang, Lixing Liu, Jianping Li, Xin Yang
article en
1 citations

Abstract

In order to enhance orchard agricultural efficiency and lower fruit production expenses, we propose a BL-DBO (Beetle Optimization Algorithm introducing Bernoulli mapping and Lévy flights) to solve the agricultural machinery dispatching model within the orchard area. First, we analyze the agricultural machinery dispatching problem in the orchard area and establish its mathematical model with the objective of minimizing dispatching costs as a constraint. To tackle the problems of uneven individual position distribution and the risk of becoming stuck in local optimal solutions in the traditional DBO algorithm, we introduce Bernoulli mapping during the initialization phase of the DBO. This method ensures a uniform distribution of the initialized population. Furthermore, during the iterative process of the algorithm, we incorporated the Lévy flight approach into the positional update equations for beetles involved in breeding, foraging, and theft activities within the DBO. This helps the beetles escape from local optimal solutions. Finally, we conduct experiments based on location information of Shunping Shunnong Orchard and fruit trees in Shijiazhuang. The results indicate that, compared to dispatching using human experience and the traditional DBO algorithm, the dispatching results generated by the BL-DBO not only reduce the number of agricultural machinery purchases but also decrease the energy loss from non-working distances of the machinery, effectively saving fruit production costs.

AgronomyVol. 15(2)
Hebei Agricultural University (CN)
Openalex Percentile: Top 25%
Advanced Algorithms and Applications
1.21
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Construction of Orchard Agricultural Machinery Dispatching Model Based on Improved Beetle Optimization Algorithm — Hongjie Liu, Pengfei Wang, et al. · Agronomy (2025) | TGRS Research Map | TGRS