应用于替代乳牛问题的数学方法:一个范围审查
Osvaldo Palma1,2, Lluis M Plà-Aragonés1,3, Alejandro Mac Cawley4
1Department of Mathematics, Universidad de Lleida, 73 Jaume II, 25001 Lleida, Spain.
Animals : an open access journal from MDPI
|April 12, 2025
概括
数学建模优化了奶牛替代策略,动态编程和模拟是关键. 未来的研究应该探索机器学习和动物健康因素,以提高农场的效率和可持续性.
科学领域:
- 农业科学 农业科学
- 运营研究 运营研究
- 数据科学数据科学数据科学
背景情况:
- 奶牛养殖依赖于战略替代决策,以实现利能力和效率.
- 数学建模为优化这些复杂决策提供了一个强大的框架.
- 需要进行全面的审查,以了解当前替代乳牛的建模方法.
研究的目的:
- 系统地审查和识别乳牛替代模型中使用的数学方法.
- 为这个领域的未来研究方向奠定基础.
- 分析常用的优化技术和响应变量.
主要方法:
- 综合范围审查来自Web of Science和Scopus数据库的同行评审文章.
- 系统地选标题,关键词和全文,以确定它们与奶牛替代模型的相关性.
- 包括40篇精选的英语文章.
主要成果:
- 动态编程 (58%) 和随机模拟 (40%) 是最常见的优化技术.
- 牛奶生产 (58%) 和利 (78%) 分别是主要响应变量和经济指标.
- 机器学习和混合方法未得到充分利用 (5%).
结论:
- 数学建模,特别是动态编程和模拟,对于提高奶牛场效率,利能力和可持续性至关重要.
- 未来的研究应该整合机器学习,混合模型,并考虑动物健康和特征.
- 扩大先进的计算方法的应用,可以进一步优化奶牛群管理.
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