Author(s)

Hongye Luo ¹, Yinren Jiang ¹

Affiliation(s)

¹ Faculty of Computational Mathematics and Cybernetics, Shenzhen MSU-BIT University, Shenzhen, 518172, China

Corresponding Author

Hongye Luo

ABSTRACT

In recent years, with the growing demand for efficient planting strategies in agricultural production, traditional models have become insufficient to meet the requirements of modern agriculture. Optimizing crop planting to achieve profit maximization has become a critical issue. To enhance the economic benefits of rural crop planting, this paper uses data from a village in North China for the year 2023 and applies a linear programming model to optimize single-season and double-season crops separately. For single-season crops, the model optimizes crops suitable for flat dry land, terraced fields, and hillside areas to achieve maximum single-season profits. For double-season crops, the model optimizes crops suitable for water-irrigated land and greenhouses, divided into the first and second seasons, considering different crops and planting strategies. The maximum profit obtained from this optimization is 51,142,487 yuan. Subsequently, this paper employs Monte Carlo simulation to predict the demand and related data for various crops from 2024 to 2030. Convergence analysis is conducted to validate the reliability of the Monte Carlo simulation results. These forecasted data are then integrated with the linear programming model established earlier to optimize planting strategies and achieve overall profit maximization. The final maximum profit reached is 55,701,493 yuan.

KEYWORDS

Linear Programming, Optimizing Crop Planting, Maximizing Rural Profits, Monte Carlo simulation

CITE THIS PAPER

Hongye Luo, Yinren Jiang, Research on Rural Crop Planting Strategies Based on Linear Programming and Monte Carlo Simulation. Agricultural & Forestry Economics and Management (2025) Vol. 8: 32-38. DOI: http://dx.doi.org/10.23977/agrfem.2025.080105.

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