Author(s)

Tong Chen

Affiliation(s)

International Business College, South China Normal University, Guangzhou 510631, Guangdong, China.

Corresponding Author

Tong Chen

ABSTRACT

This study focuses on optimizing crop planning in a mountainous village in North China, where the cold climate permits only one growing season per year. The village’s arable land is distributed across 34 plots of various types, including flat drylands, terraces, slopes, and irrigated fields. A linear programming model is developed to maximize planting revenue, considering crop rotation requirements, land suitability, planting costs, yields, and market prices. To simulate future conditions, crop prices in 2030 are modeled using normally distributed random numbers. The model sets two sales scenarios: (1) surplus production beyond expected sales cannot be sold, resulting in waste; and (2) surplus is sold at 50% of the 2023 market price. To address uncertainties in yield, cost, price, and demand, as well as potential planting risks, a particle swarm optimization algorithm is employed with random factors to simulate changing conditions. Results show that the village can achieve annual revenues between 8 to 9 million RMB under both deterministic and stochastic scenarios. The optimized strategies satisfy agronomic and environmental constraints and offer scientific support for sustainable agricultural development in resource-limited mountainous regions.

KEYWORDS

Crop cultivation; Optimal planting strategy; Linear programming particle swarm algorithm; Multiple regression modeling

CITE THIS PAPER

Tong Chen. Sustainable crop planning in a mountainous village using linear programming. Eurasia Journal of Science and Technology. 2025, 7(3): 53-59. DOI: https://doi.org/10.61784/ejst3092.

REFERENCES

[1] LIN Dayan, ZHU Jing. Reasons for changes in the planting structure of major crops in China from the perspective of supply elasticity. Agricultural Technology and Economy, 2015(01): 33-41.

[2] HU Yunfei, LIU Xu, LIANG Junfen, et al. Spatial and temporal evolution of crop cropping structure in the Guangdong-Hong Kong-Macao Greater Bay Area from 1990 to 2020. Guangdong Agricultural Science, 2023, 50(01): 13-27.

[3] AN Yue, TAN Xuelan, TAN Jieyang, et al. Evolution of crop planting structure and influencing factors in Hunan Province. Economic Geography, 2021, 41(02): 156-166.

[4] Zhou XG. Analysis of the impact of agricultural planting factors on agricultural planting structure. Rural Practical Technology, 2023(10): 99-100.

[5] SONG Yu, LIU Weiping. Influencing factors and multivariate paths of the evolution of cultivated land planting structure - A qualitative comparative analysis of fuzzy sets based on case zones in 30 provinces. Geographic Research and Development, 2024, 43(04): 133-138.

[6] Bao Shuzong. Influence of agricultural planting factors on planting structure and optimization strategy. Agriculture and Technology, 2020, 40(13): 90-91.

[7] LUO Qiancheng,WANG Yuexiang,CHI Wenfeng,et al. Factors affecting the evolution of crop cropping structure in the black soil area of Inner Mongolia. Resource Science, 2023, 45(05): 994-1005.

[8] WU Menghan,WANG Yi. Optimized adjustment of multi-objective planting of crops in Shache Irrigation District of Xinjiang. People's Yellow River, 2024, 46(01): 120 125+131.

[9] ZHANG Hao Yang,CHEN Xing. Optimal planting structure preference method for irrigation areas under water right constraints. Modern Agricultural Science and Technology, 2024(24): 161-164.

[10] An Jinping. Application of linear programming in economic analysis. Journal of Central University of Finance and Economics, 2005(01): 44-47.

[11] Deng Chan,Li Chun,Li Mengqi, et al. Progress of particle swarm algorithm in agricultural hydrology. Anhui Agricultural Science,2021, 49(08): 16-20+29.