THE OPTIMAL YIELD PROBLEM OF CROP PLANTING BASED ON LINEAR PROGRAMMING MODEL
Volume 7, Issue 2, Pp 20-27, 2025
DOI: https://doi.org/10.61784/ejst3072
Author(s)
Jie Deng1, Jian Wang1, Hao Xu1, ZhengBo Li2*
Affiliation(s)
1Department of Brewing Engineering, MouTai Institute, Renhuai 564500, GuiZhou, China.
2Department of Public Basic Education, MouTai Institute, Renhuai 564500, GuiZhou, China.
Corresponding Author
ZhengBo Li
ABSTRACT
The optimal income problem of crop planting is controlled by various uncertain factors. By controlling for uncertain factors, the problem of crop income can be summarized as the optimization problem of crop planting structure. Reasonable optimization of crop planting structure has an important impact on the economic status of regional farmers, sustainable development of agriculture, and sustainable utilization of land resources. The crop planting structure includes both temporal and spatial structures. Therefore, this article constructs a mathematical model combining linear programming and Monte Carlo method by analyzing the two types of land structures. Firstly, use linear programming to simulate various constraints in crop planting structure, and then increase the randomness in time structure through Monte Carlo method. At the same time, this article also explores the correlation between crop yield per mu, planting cost, and sales price through heat maps, in order to help decision-makers better analyze crop planting structure and improve crop planting income. The results indicate that optimizing the crop planting structure can improve crop yields and provide reference for decision-makers in crop planting planning and market pricing.
KEYWORDS
Crop planting structure; Linear programming; Monte carlo method; Heat map correlation
CITE THIS PAPER
Jie Deng, Jian Wang, Hao Xu, ZhengBo Li. The optimal yield problem of crop planting based on linear programming model. Eurasia Journal of Science and Technology. 2025, 7(2): 20-27. DOI: https://doi.org/10.61784/ejst3072.
REFERENCES
[1] Hu M, Tang H, Yu Q, et al. A new approach for spatial optimization of crop planting structure to balance economic and environmental benefits. Sustainable Production and Consumption, 2025, 53: 109-124.
[2] Liu Q, Niu J, Du T, et al. A full-scale optimization of a crop spatial planting structure and its associated effects. Engineering, 2023, 28: 139-152.
[3] Adamo T, Colizzi L, Dimauro G, et al. Crop planting layout optimization in sustainable agriculture: A constraint programming approach. Computers and Electronics in Agriculture, 2024, 224: 109162.
[4] Alotaibi A, Nadeem F. A review of applications of linear programming to optimize agricultural solutions. International Journal of Information Engineering and Electronic Business, 2021, 15(2): 11.
[5] Adeyemo J, Otieno F. Optimizing planting areas using differential evolution (DE) and linear programming (LP). International Journal of Physical Sciences, 2009, 4(4): 212-220.
[6] Li M, Cao X, Liu D, et al. Sustainable management of agricultural water and landresources under changing climate and socio-economic conditions: A multi-dimensional optimization approach. Agricultural Water Management, 2022, 259: 107235.
[7] Abdelwahab H F, Negm A M, Ramadan E M, et al. Mitigating water shortages and enhancing food security through crop optimization: Insights from the Eastern Nile Delta. 2024.
[8] Reddy D J, Kumar M R. Crop yield prediction using machine learning algorithm//2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS). IEEE, 2021: 1466-1470.
[9] Luo N, Meng Q, Feng P, et al. China can be self-sufficient in maize production by 2030 with optimal crop management. Nature Communications, 2023, 14(1): 2637.
[10] Gebre S L, Cattrysse D, Alemayehu E, et al. Multicriteria decision making methods to address rural land allocation problems: A systematic review. International Soil and Water Conservation Research, 2021, 9(4): 490-501.
[11] Dantzig G B. Linear programming. Operations research, 2002, 50(1): 42-47.
[12] Pramesti F A, Subekti H, Candra A D. Application of Monte Carlo simulation for the estimation of production availability in geothermal well//IOP Conference Series: Earth and Environmental Science. IOP Publishing, 2024, 1339(1): 012017.
[13] Zhu S G, Cheng Z G, Wang J, et al. Soil phosphorus availability and utilization are mediated by plant facilitation via rhizosphere interactions in an intercropping system. European Journal of Agronomy, 2023, 142: 126679.
[14] Ma L, Ma S, Chen G, et al. Mechanisms and mitigation strategies for the occurrence of continuous cropping obstacles of legumes in China. Agronomy, 2023, 14(1): 104.
[15] Moldavan L, Pimenowa O, Wasilewski M, et al. Crop rotation management in the context of sustainable development of agriculture in Ukraine. Agriculture, 2024, 14(6): 934.
[16] Ginn W. Agricultural fluctuations and global economic conditions. Review of World Economics, 2024, 160(3): 1037-1056.