An optimization problem Based on Integer Programming Theory

Hui Wang, Xiaoqing Ji, Quanbo Sheng, Jingjing Zhao, Mengwei Wang
Proceedings of 2025 2nd International Conference on Machine Learning and Intelligent Computing, PMLR 278:819-825, 2025.

Abstract

With the implementation of the rural revitalization strategy, promoting high-quality rural development has become a strategic requirement. A key challenge in optimizing rural development is achieving high-quality agricultural cultivation. Given fixed arable land areas and seed quality, determining optimal crop planting strategies is a critical research focus. This study takes a village in North China’s mountainous region as an example, incorporating local land types, suitable crops, terrain areas, and infrastructure (traditional greenhouses and smart greenhouses). First, land is classified based on given data. Second, yields, planting costs, and sales prices of the same crop across different terrains are analyzed, with median prices used for profit comparisons. Finally, using integer programming principles and intelligent software, an optimal planting strategy for 2024 is proposed through yield models, planting area models, and maximum revenue models.

Cite this Paper

BibTeX
@InProceedings{pmlr-v278-wang25i, title = {An optimization problem Based on Integer Programming Theory}, author = {Wang, Hui and Ji, Xiaoqing and Sheng, Quanbo and Zhao, Jingjing and Wang, Mengwei}, booktitle = {Proceedings of 2025 2nd International Conference on Machine Learning and Intelligent Computing}, pages = {819--825}, year = {2025}, editor = {Zeng, Nianyin and Pachori, Ram Bilas and Wang, Dongshu}, volume = {278}, series = {Proceedings of Machine Learning Research}, month = {25--27 Apr}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v278/main/assets/wang25i/wang25i.pdf}, url = {https://proceedings.mlr.press/v278/wang25i.html}, abstract = {With the implementation of the rural revitalization strategy, promoting high-quality rural development has become a strategic requirement. A key challenge in optimizing rural development is achieving high-quality agricultural cultivation. Given fixed arable land areas and seed quality, determining optimal crop planting strategies is a critical research focus. This study takes a village in North China’s mountainous region as an example, incorporating local land types, suitable crops, terrain areas, and infrastructure (traditional greenhouses and smart greenhouses). First, land is classified based on given data. Second, yields, planting costs, and sales prices of the same crop across different terrains are analyzed, with median prices used for profit comparisons. Finally, using integer programming principles and intelligent software, an optimal planting strategy for 2024 is proposed through yield models, planting area models, and maximum revenue models.} }
Endnote
%0 Conference Paper %T An optimization problem Based on Integer Programming Theory %A Hui Wang %A Xiaoqing Ji %A Quanbo Sheng %A Jingjing Zhao %A Mengwei Wang %B Proceedings of 2025 2nd International Conference on Machine Learning and Intelligent Computing %C Proceedings of Machine Learning Research %D 2025 %E Nianyin Zeng %E Ram Bilas Pachori %E Dongshu Wang %F pmlr-v278-wang25i %I PMLR %P 819--825 %U https://proceedings.mlr.press/v278/wang25i.html %V 278 %X With the implementation of the rural revitalization strategy, promoting high-quality rural development has become a strategic requirement. A key challenge in optimizing rural development is achieving high-quality agricultural cultivation. Given fixed arable land areas and seed quality, determining optimal crop planting strategies is a critical research focus. This study takes a village in North China’s mountainous region as an example, incorporating local land types, suitable crops, terrain areas, and infrastructure (traditional greenhouses and smart greenhouses). First, land is classified based on given data. Second, yields, planting costs, and sales prices of the same crop across different terrains are analyzed, with median prices used for profit comparisons. Finally, using integer programming principles and intelligent software, an optimal planting strategy for 2024 is proposed through yield models, planting area models, and maximum revenue models.
APA
Wang, H., Ji, X., Sheng, Q., Zhao, J. & Wang, M.. (2025). An optimization problem Based on Integer Programming Theory. Proceedings of 2025 2nd International Conference on Machine Learning and Intelligent Computing, in Proceedings of Machine Learning Research 278:819-825 Available from https://proceedings.mlr.press/v278/wang25i.html.

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