Author(s)

YiShuo Jing^*

Affiliation(s)

College of Economics and Management, Tianjin University of Science and Technology, Tianjin 300222, China.

Corresponding Author

YiShuo Jing

ABSTRACT

As a key agricultural region in China, the development of organic farming in North China has a profound impact on promoting sustainable rural economic growth, enhancing farmers 'quality of life, and advancing the construction of beautiful villages. This paper focuses on the application of dynamic programming models for the utilization strategies of arable land resources in the organic farming industry in North China. By using dynamic programming models, it provides tailored solutions to the specific conditions of rural areas, considering factors such as time, resources, and costs, to develop planting strategies that achieve optimal results under various conditions. During the model construction process, the climate characteristics of North China and the special requirements of organic farming are fully considered. Monte Carlo simulation algorithms are used for iterative screening, followed by adjustments based on elastic demand theory to select the best planting strategy. The application of this dynamic programming model not only enhances the production efficiency of organic farming but also reduces planting risks due to changes in climate and market conditions. It also promotes the rational allocation and efficient use of agricultural resources. By optimizing the utilization strategies of arable land resources, it lays a solid foundation for the sustainable development of the organic farming industry in North China's rural areas, contributing to the goals of rural revitalization and the construction of beautiful villages.

KEYWORDS

Cultivated land resources; Organic farming; Dynamic planning; Sustainable development

CITE THIS PAPER

YiShuo Jing. Crop planting strategy based on dynamic planting scheme optimization model. Eurasia Journal of Science and Technology. 2025, 7(4): 49-55. DOI: https://doi.org/10.61784/ejst3103.

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