Research on the Optimal Planting Strategy of Crops Based on Nested Genetic Algorithm

Authors

  • Yishu Zhao College of Electronic Engineering, National University of Defense Technology, Hefei, China, 230027
  • Wenjie He College of Electronic Engineering, National University of Defense Technology, Hefei, China, 230027
  • Guiqiu Tan College of Electronic Engineering, National University of Defense Technology, Hefei, China, 230027
  • Jingu Qin College of Electronic Engineering, National University of Defense Technology, Hefei, China, 230027

DOI:

https://doi.org/10.54097/ttcgr388

Keywords:

Crop planting, Nested genetic algorithm, Monte Carlo simulation, TOPSIS, Spearman correlation coefficient.

Abstract

The development of organic farming tailored to the actual conditions of rural areas holds significant practical importance for sustainable rural development. This paper delves into the optimal crop planting strategies under various scenarios, including different sales methods, crop functional interrelationships and uncertainties related to production and costs, market and revenue. Initially, a multi-year total profit optimization model is constructed and solved using a nested genetic algorithm. Subsequently, the Spearman correlation coefficient was used to classify replacement crops and complementary crops to explore the influence of crop functional interrelationships on planting plan and yield. Finally, synthetic aperture radar (SAR) monitoring data is incorporated to assess fluctuations in crop yield per unit area, and the Monte Carlo method is employed to simulate uncertain parameters. Statistical metrics of preselected schemes are analyzed using the TOPSIS method, with the optimal planting strategy ultimately derived by integrating growers' risk preferences.

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References

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Published

19-10-2025

Issue

Vol. 156 (2025): 4th International Conference on Architecture, Geotechnical Engineering and Construction Technology (AGECT 2025)

Section

Articles

License

Copyright (c) 2025 Highlights in Science, Engineering and Technology

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite

Zhao, Y., He, W., Tan, G., & Qin, J. (2025). Research on the Optimal Planting Strategy of Crops Based on Nested Genetic Algorithm. Highlights in Science, Engineering and Technology, 156, 76-86. https://doi.org/10.54097/ttcgr388