Research On Maximizing Crop Planting Returns Based on Genetic Algorithm

With the rapid development of agricultural modernization, the traditional planting method relying on experience makes it difficult to effectively cope with market fluctuations and uneven distribution of resources, resulting in the difficulty of maximizing agricultural returns. To solve this problem, some crop data were pre-processed and the extreme values in the data were processed by IQR (Interquartile Range). On this basis, the agricultural planting income maximization model was constructed, and the Genetic Algorithm (GA) was used to optimize the model's prediction. Through genetic operations such as selection, crossover, and mutation, the planting plan was gradually optimized, and the optimal planting planning plan for a rural plot in 2024 was finally obtained. For example, plot A1 with an area of 85 acres of arid land is suitable for growing sorghum, and plot A2 with 55 acres is ideal for growing red beans. The results of this study provide a reference value for the optimization of agricultural planting and are of great significance for improving the efficiency and income of rural resource utilization.

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Publication Details

Journal
Highlights in Business Economics and Management
Published
2025-03-17
DOI
https://doi.org/10.54097/nx2nj306
Primary Topic
Regional Economic and Spatial Analysis
Type
article
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article

Research On Maximizing Crop Planting Returns Based on Genetic Algorithm

C. H. Bheemasankara Rao
Highlights in Business Economics and Management
Regional Economic and Spatial Analysis
article

Research On Maximizing Crop Planting Returns Based on Genetic Algorithm

C. H. Bheemasankara Rao
article en

Abstract

With the rapid development of agricultural modernization, the traditional planting method relying on experience makes it difficult to effectively cope with market fluctuations and uneven distribution of resources, resulting in the difficulty of maximizing agricultural returns. To solve this problem, some crop data were pre-processed and the extreme values in the data were processed by IQR (Interquartile Range). On this basis, the agricultural planting income maximization model was constructed, and the Genetic Algorithm (GA) was used to optimize the model's prediction. Through genetic operations such as selection, crossover, and mutation, the planting plan was gradually optimized, and the optimal planting planning plan for a rural plot in 2024 was finally obtained. For example, plot A1 with an area of 85 acres of arid land is suitable for growing sorghum, and plot A2 with 55 acres is ideal for growing red beans. The results of this study provide a reference value for the optimization of agricultural planting and are of great significance for improving the efficiency and income of rural resource utilization.

Highlights in Business Economics and ManagementVol. 53
Changchun University of Science and Technology (CN)
Openalex Percentile: Top 88%
Regional Economic and Spatial Analysis
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Research On Maximizing Crop Planting Returns Based on Genetic Algorithm — C. H. Bheemasankara Rao · Highlights in Business Economics and Management (2025) | TGRS Research Map | TGRS