Author(s)

Hengtian Ma

Corresponding Author

Hengtian Ma

Abstract

This study presents a comprehensive analysis and optimization of crop planting strategies for a village in the North China mountainous area, utilizing a multi-year planning model that integrates linear programming and Monte Carlo simulation. The research aims to maximize economic benefits by considering various factors such as land types, planting seasons, crop yields, and market demands. The dataset encompasses detailed information on arable land, greenhouses, and crop cultivation for the year 2023, which includes planting areas, seasons, yields per acre, planting costs, and sales prices. The study employs a multi-stage planning model that establishes an objective function to maximize profits, considering sales revenue and planting costs. The model is subject to constraints such as land availability, crop yield limitations, scale of planting, intercropping practices, and crop rotation requirements. A key aspect of the model is the inclusion of legumes in the planting plan every three years to maintain soil fertility. To address market uncertainties, a Monte Carlo simulation is applied to account for fluctuations in crop yields, cost prices, sales prices, and sales volumes. This simulation assists in deriving optimal planting plans under varying market conditions, ensuring adaptability and risk mitigation. The simulation process involves parameter initialization, random variation generation within specified ranges, and repeated trials to achieve statistically significant results.

Keywords

Crop planting strategy, Linear programming, Monte Carlo simulation, Agricultural optimization, Market volatility