Research on Planting Strategies for Crops in the Mountainous Areas of North China

This study focuses on the planning of rural planting strategies in the mountainous regions of North China from 2024 to 2030, with the core objective of addressing market dynamics, enhancing the economic benefits of agricultural output, and promoting the sustainable development of rural economies. The research employs data preprocessing and visualization techniques to abstract practical issues into a 0-1 linear programming model, aiming for profit maximization as the optimization goal while incorporating multiple constraints to refine planting strategies. Ultimately, this study utilizes the Monte Carlo simulation method for randomized crop selection, visualizes yield data in relation to the planting area of each farmland, and integrates the results into tabular formats. Furthermore, the study provides practical insights and optimization strategies based on empirical analysis.

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Publication Details

Journal
Mathematical Modeling and Algorithm Application
Published
2025-10-09
DOI
https://doi.org/10.54097/tz3xqs55
Primary Topic
Forest, Soil, and Plant Ecology in China
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on Planting Strategies for Crops in the Mountainous Areas of North China

Xiaotong Jiang
Mathematical Modeling and Algorithm Application
Forest, Soil, and Plant Ecology in China
article

Research on Planting Strategies for Crops in the Mountainous Areas of North China

Xiaotong Jiang
article en

Abstract

This study focuses on the planning of rural planting strategies in the mountainous regions of North China from 2024 to 2030, with the core objective of addressing market dynamics, enhancing the economic benefits of agricultural output, and promoting the sustainable development of rural economies. The research employs data preprocessing and visualization techniques to abstract practical issues into a 0-1 linear programming model, aiming for profit maximization as the optimization goal while incorporating multiple constraints to refine planting strategies. Ultimately, this study utilizes the Monte Carlo simulation method for randomized crop selection, visualizes yield data in relation to the planting area of each farmland, and integrates the results into tabular formats. Furthermore, the study provides practical insights and optimization strategies based on empirical analysis.

Mathematical Modeling and Algorithm ApplicationVol. 6(1)
Beijing University of Chinese Medicine (CN)
Openalex Percentile: Top 68%
Forest, Soil, and Plant Ecology in China
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