Optimization strategy of crop cultivation in North China based on sample mean approximation

Jingjing Lin

doi:10.54097/yay2x744

Authors

Jingjing Lin

DOI:

https://doi.org/10.54097/yay2x744

Keywords:

Crop Planting Optimization Strategy, Linear Programming, Sample Average Approximation, Latin Hypercube Sampling.

Abstract

Optimizing native resources can enhance productivity, improve farmers' living standards and promote ecological conservation. The aim of this paper is to analyze the characteristics of crop cultivation in North China and propose an optimized cultivation strategy to achieve maximum total returns during the period 2024-2030. The study adopts the Sample Average Approximation (SAA) method in stochastic optimization, combined with Latin hypercube sampling, to obtain the optimal planting plan using linear programming by considering constraints such as crop planting area, crop rotation requirements and legume planting. The results show that the optimized planting scheme can achieve an increase in average annual income compared with the ideal situation, and the total income is increased by 81.46% compared with the pre-optimization situation. The study shows that the optimized planting strategy not only improves the economic benefits but also provides a practical reference for the future revitalization of the countryside, which is of great potential for application and research value.

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