Research on Optimization Strategies of Agricultural Cultivation Based on Linear Programming Models and Monte Carlo Methods

Abstract

A rural village in China faces multiple challenges, including perennially low temperatures, limitations on the type and amount of arable land, and crop growth patterns. These factors lead to increased difficulty in marketing crops, especially in the stagnant marketing problem, which affects the sustainable development of the agricultural economy. In this paper, a linear programming model is developed for the stagnant marketing problem, and various constraints (e.g., total plot size, minimum cropland area restrictions, crop rotation requirements, etc.) are set to maximize the total return. For uncertainties, the Monte Carlo algorithm is applied to simulate and generate multiple potential scenarios to analyze the optimal planting strategy. By solving the model, this article identified the optimal planting plan under different treatment scenarios, as well as proposed countermeasures to cope with the effects of uncertainties. Overall, this study provides systematic solutions to address the challenges facing rural agriculture in China and valuable cases and references for economic efficiency improvement and sustainable development in the agricultural sector.