Planting Optimization in the Northern China Based on 0-1 Programming

Yu Zheng

doi:10.54097/tmq7nx33

Authors

Yu Zheng

DOI:

https://doi.org/10.54097/tmq7nx33

Keywords:

Monte Carlo Algorithms, Planting Optimization Strategy, 0-1 Programming.

Abstract

In order to comprehensively promote the development of agricultural modernization and ensure the sustainability of Rural Revitalization land in North China, this paper will propose a general mathematical model according to the realistic natural constraints of rural areas in mountainous areas of North China, in order to improve the total agricultural income. Through the establishment of 0-1 integer programming model and nonlinear model, the rural crop planting strategy in China from 2024 to 2030 was optimized. Finally, the overall profit of the model shows an upward trend, which is similar to the development trend of China's agricultural product market. The model can flexibly adapt to the changes of market and natural conditions, and has good scalability, which can provide help for the construction of agricultural power.

Downloads

Download data is not yet available.

References

[1] Bren d’Amour C, Reitsma F, Baiocchi G, et al. Future urban land expansion and implications for global croplands [J]. Proceedings of the National Academy of Sciences, 2017, 114 (34): 8939 - 8944.

[2] Deng X, Huang J, Rozelle S, et al. Impact of urbanization on cultivated land changes in China [J]. Land use policy, 2015, 45: 1 - 7.

[3] Li C, Wang X, Ji Z, et al. Optimizing the use of cultivated land in China’s main grain-producing areas from the dual perspective of ecological security and leading-function zoning [J]. International Journal of Environmental Research and Public Health, 2022, 19 (20): 13630.

[4] Yu Y, Lin J, Zhou P, et al. Cultivated Land Input Behavior of Different Types of Rural Households and Its Impact on Cultivated Land-Use Efficiency: A Case Study of the Yimeng Mountain Area, China [J]. International Journal of Environmental Research and Public Health, 2022, 19 (22): 14870.

[5] Huang L, Liu J, Shao Q, et al. Carbon sequestration by forestation across China: Past, present, and future [J]. Renewable and Sustainable Energy Reviews, 2012, 16 (2): 1291 - 1299.

[6] Karaman N, Aksoy S, Cesur F, et al. Determining the effect of urbanization on agricultural lands using Remote Sensing and Geographic Information System techniques [J]. 2022.

[7] Seto K C, Ramankutty N. Hidden linkages between urbanization and food systems [J]. Science, 2016, 352 (6288): 943 - 945.

[8] Yang D, Liu Z, Zhang P, et al. Understanding Relationships between Cultivated Land Pressure and Economic Development Level across Spatiotemporal Characteristics: Implications for Supporting Land-Use Management Decisions [J]. International Journal of Environmental Research and Public Health, 2022, 19 (23): 16362.

[9] Wang S, Bai X, Zhang X, et al. Urbanization can benefit agricultural production with large-scale farming in China [J]. Nature Food, 2021, 2 (3): 183 - 191.

[10] Yao J, Li C, Xiao C. Swift Sampler: Efficient Learning of Sampler by 10 Parameters [J]. arxiv preprint arxiv: 2410.05578, 2024.

[11] Yao J, Zhang J. Depthssc: Depth-spatial alignment and dynamic voxel resolution for monocular 3d semantic scene completion [J]. arXiv preprint arXiv: 2311.17084, 2023.

[12] Hou X, Liu J, Zhang D, et al. Impact of urbanization on the eco-efficiency of cultivated land utilization: A case study on the Yangtze River Economic Belt, China [J]. Journal of Cleaner Production, 2019, 238: 117916.

[13] Hong M Y, Zheng L N. Regional differences and spatiotemporal and characteristics of agricultural eco-efficiency in China [J]. Stat. Decis, 2020, 36: 56 - 61.