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Integrating Proactive and Reactive Operating Room Management

Integrating Proactive and Reactive Operating Room Management
集成主动式和被动式手术室管理
批准号:
1333758
负责人:
Oleg Prokopyev
金额:
$35.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-10-01 至 2017-09-30

项目摘要

项目成果

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中文摘要
翻译
该奖项的研究目标是制定,校准和解决手术室(OR)调度模型,可以适应意外事件,如异常长的程序或病人?没有演出这些模型将产生初始时间表,以促进手术日开始后的灵活反应,包括将手术转移到不同的手术室和/或时间段。不幸的是,这种数学模型的灵活性增加是有代价的:这种模型非常难以解决,现有的技术肯定会失败,即使是很小的例子。可扩展性将包括可概括的见解或时间表的哪些方面使他们灵活,和各种广泛适用的技术来解决这些困难的问题,以及密切相关的规划问题下产生的不确定性在不同的领域。美国的医疗保健成本继续大幅上升,手术占这些成本的很大一部分。如果成功的话,本研究的结果将为设计适应性强、灵活性强的手术室时间表提供方法。我们预计,有很大的机会,优化外科手术,从而节省显着。这项建议的教育影响将使多个群体受益。我们将把这项研究的结果纳入针对不同层次的课程。学生和医学研究人员也将通过指导和他们直接参与研究工作,包括通过REU计划本科生的参与进行培训。
英文摘要
The research objective of this award is to formulate, calibrate and solve operating room (OR) scheduling models that can adapt to unexpected events, such as unusually long procedures or patient ?no shows.? These models will produce initial schedules that will facilitate flexible reactions after the surgical day has begun, including moving procedures to different operating rooms and/or time slots. Unfortunately, the increased flexibility of such mathematical models comes at a cost: such models are very difficult to solve and existing techniques are sure to fail on even small examples. Deliverables will include generalizable insights into what aspects of OR schedules make them flexible, and a variety of widely applicable techniques for solving these difficult problems, as well as closely related planning problems under uncertainty arising in different domains. Healthcare costs in the US continue to rise significantly, and surgery accounts for a large portion of these costs. If successful, the results of this research will provide approaches for the design of OR schedules that are adaptable and flexible in response to unexpected events. We anticipate that there are large opportunities for optimizing surgical procedures, resulting in significant savings. The educational impacts of this proposal will benefit multiple groups. We will incorporate results of this research into courses aimed at a variety of levels. Students and medical researchers will be also trained through mentoring and their direct involvement in the research work, including the participation of undergraduate students via the REU program.
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Bilevel Optimization with Learning
  • 批准号:
    1634835
  • 项目类别:
    Standard Grant
  • 资助金额:
    $22.76万
  • 财政年份:
    2016
  • 负责人:
    Oleg Prokopyev
  • 依托单位:
Collaborative Research: International Experience for Students: U.S.-Ukraine Collaboration on Discrete and Nondifferentiable Optimization
  • 批准号:
    0853997
  • 项目类别:
    Standard Grant
  • 资助金额:
    $6.45万
  • 财政年份:
    2009
  • 负责人:
    Oleg Prokopyev
  • 依托单位:
Novel Optimization-Based Biclustering Algorithms for Biomedical Data Analysis
  • 批准号:
    0825993
  • 项目类别:
    Standard Grant
  • 资助金额:
    $21.28万
  • 财政年份:
    2008
  • 负责人:
    Oleg Prokopyev
  • 依托单位:
海外基金