使用元启发学和混合整数线性编程进行医院内患者运输的路线规划
Saran Karthikeyan1, Sasanka Potluri1
1Institute for Medical Statistics, Informatics, and Data Science, Jena University Hospital, Bachstraße 18, 07743, Jena, Thüringen, Germany.
Studies in health technology and informatics
|August 23, 2024
概括
这项研究利用先进的算法优化了医院内的患者运输路线. 开发的方法有效地将工作分配给运输商,最大限度地减少旅行和置时间,以改善医疗保健物流.
科学领域:
- 医疗保健 运营 研究 研究 研究
- 优化物流的优化物流.
- 医院管理系统 医院管理系统
背景情况:
- 医疗保健服务涉及复杂的过程,影响患者护理质量.
- 患者的运输,无论是医院间还是医院内,都是一个关键的后勤挑战.
- 现有的医院内部运输路线规划面临来自动态因素和公平考虑的复杂性.
研究的目的:
- 确定医院内患者运输所需的运输器的最佳数量.
- 为所有运输商生成高效的路线计划,在轮班内分配工作.
- 为了最大限度地减少运输商之间的总旅行时间,置时间和旅行时间偏差.
主要方法:
- 利用多个阶段的本地搜索元启发来实现主要目标.
- 综合混合整数线性编程用于公平的职位分配和约束表述.
- 整合优化约束来满足次要目标,包括尽量减少旅行和置时间.
主要成果:
- 成功确定了可行的运输机数量,并生成了优化的路线计划.
- 实现了运输商总旅行和置时间的显著减少.
- 在所有运输商中证明了总旅行时间的最小偏差,确保工作负载公平.
- 优化约束有效地平衡了路线规划中的多个目标.
结论:
- 拟议的多阶段局部搜索元启发与混合整数线性编程为医院内患者运输提供了强大的解决方案.
- 该方法提高了医院内患者运输物流的效率和公平性.
- 这种方法通过优化资源配置和减少运营效率低下,提高了医疗保健服务质量.
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