Research on Optimization of Crop Planting Strategies Based on Linear Programming and Monte Carlo Methods Abstract

Yibo Shang

doi:10.62051/fyqb2856

Authors

Yibo Shang

DOI:

https://doi.org/10.62051/fyqb2856

Keywords:

Crop planting strategies; Monte Carlo simulation; linear programming.

Abstract

With global population growth and climate change impacting agriculture, optimizing crop planting strategies is essential. This study aims to maximize net returns from limited land and climatic conditions using a linear programming model combined with Monte Carlo simulation. Two scenarios were considered: excess yield either wasted or sold at a reduced price. By simulating various planting strategies, the optimal scheme was identified. The results indicated that the highest total return of 9,323,486.21 was achieved in 2025, while the return in 2028 was lower at 8,695,777.98. This research provides valuable insights into improving agricultural productivity and profitability.

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