Optimization of Crop Planting Strategies Based on Monte Carlo Simulation and Greedy Algorithm

Authors

  • Qisen Wang
  • Junhan Hou
  • Zihe Zhong

DOI:

https://doi.org/10.54097/5as5pd83

Keywords:

Goal Programming Model, Monte Carlo Simulation, Time Series Regression, Greedy Algorithm, Pearson Correlation Coefficient

Abstract

Based on Monte Carlo simulation and greedy algorithm, this paper explores the optimization scheme of crop planting under different conditions. First, for the planting scheme under stable market conditions, this paper establishes an objective planning model to optimize the planting plan from 2024 to 2030 by maximizing the annual planting revenue and combining the constraints of various economic indicators. Further, considering that part of the crop may be stagnant or sold at a discounted price, this paper explores the impacts of different sales scenarios on the planting strategy. Then, for the planting strategy under uncertainty, this paper uses Monte Carlo simulation and time series regression analysis to predict various economic parameters of crops, and based on this prediction result, the greedy algorithm is applied to optimize the planting plan. Finally, the planting scheme is further optimized by considering the complementarity and substitutability between crops and combining the correlation between the indicators of crops.

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References

[1] Zhang Juankang. Discussion on scientific planting and pest control technology of crops[J]. Hebei Agriculture,2024, (11): 74-75.

[2] LI Mo, Guo Ping. Research on multi-objective modeling of planting structure based on two-layer fractional planning[J]. Journal of Agricultural Machinery,2014,45(09):168-174+130.

[3] Deng Shuo. Practical exploration of Monte Carlo method in cultivating students' computational thinking[J]. China Modern Education Equipment,2024, (16):45-48. DOI: 10. 13492/ j. cnki. cmee. 2024.16.014.

[4] Yang Yue Tao. Time series modeling research on the impact of minimum purchase price on grain planting area[J]. Xueyuan, 2016, (36):123-125+141.

[5] Zhao Yuanshang, Lin Weifang. Research on typical scenarios based on Pearson correlation coefficient fusion density peak and entropy weight method[J]. China Electric Power, 2023, 56 (05): 193-202.

[6] Meng Xiangchao. Research on production decision-making of facility agriculture production units based on greedy algorithm [D]. Nanjing Agricultural University,2016.

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Published

21-01-2025

Issue

Section

Articles

How to Cite

Wang, Q., Hou, J., & Zhong, Z. (2025). Optimization of Crop Planting Strategies Based on Monte Carlo Simulation and Greedy Algorithm. Frontiers in Computing and Intelligent Systems, 11(1), 73-79. https://doi.org/10.54097/5as5pd83