一个混合启发式精确优化大规模的家庭医疗保健问题
IEEE/ACM transactions on computational biology and bioinformatics
|October 25, 2023
概括
一个新的混合优化算法有效地解决了在COVID-19大流行期间为家庭医疗保健 (HHC) 服务分配护士的挑战,优化了大量患者的分配.
科学领域:
- 运营研究 运营研究
- 医疗保健管理的管理
- 计算机科学 计算机科学
背景情况:
- 由于COVID-19的流行,对家庭医疗保健 (HHC) 服务的需求增加了.
- 护士资源有限和患者时间限制使HHC的护士分配变得复杂.
研究的目的:
- 开发一个有效的算法,用于大规模的家庭医疗保健护士分配.
- 优化护士任务,考虑到资源限制和患者需求.
主要方法:
- 设计了一个混合启发式精确优化框架.
- 制定了一个多目标混合整数线性编程模型.
- 实施了改进的分支和绑定算法,以提高计算速度.
主要成果:
- 拟议的算法成功优化了100多名患者的HHC问题.
- 它为不同的护士数量提供了多样化的护士分配选择.
- 该算法在大规模的HHC优化中表现优于常用方法.
结论:
- 混合优化算法为复杂的HHC护士分配提供了可行的解决方案.
- 这种方法提高了管理HHC服务的效率和灵活性.
- 这种方法对于大量患者群体和资源限制特别有效.
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