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A constraint programming-based solution approach for medical resident scheduling problems

机译:基于约束规划的医疗居民调度问题解决方案

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Persistent calls come from within the graduate medical education community and from external sources for regulating the resident duty hours in order to meet the obligations about the quality of resident education, the well-being of residents themselves, and the quality of patient care services. The report of the Accreditation Council for Graduate Medical Education (ACCME) proposes common program requirements for resident hours. In this paper, we first develop a mixed-integer programming model for scheduling residents' duty hours considering the on-call night, day-off, rest period, and total work-hour ACCME regulations as well as the demand coverage requirements of the residency program. Subsequently, we propose a column generation model that consists of a master problem and an auxiliary problem. The master problem finds a configuration of individual schedules that minimizes the sum of deviations from the desired service levels for the day and night periods. The formulation of this problem is possible by representing the feasible schedules using column variables, whereas the auxiliary problem finds the whole set of feasible schedules using constraint programming. The proposed approach has been tested on a series of problems using real data obtained from a hospital. The results indicate that high-quality schedules can be obtained within a few seconds.
机译:持续的呼叫来自研究生医学教育界内部和外部资源,以规范居民的工作时间,以履行有关居民教育质量,居民自身福祉以及患者护理服务质量的义务。研究生医学教育认证委员会(ACCME)的报告提出了住院时间的通用计划要求。在本文中,我们首先开发一种混合整数编程模型,该模型用于考虑居民的上班时间,上班时间,休息日,休息时间,总工作时间ACCME法规以及居民的需求覆盖要求程序。随后,我们提出了一个包含主问题和辅助问题的列生成模型。主要问题是找到单个时间表的配置,该配置可以最大程度地减少白天和晚上与期望服务水平的偏差总和。通过使用列变量表示可行时间表,可以制定此问题,而辅助问题可以使用约束编程来找到整个可行时间表。使用从医院获得的真实数据,对所提出的方法进行了一系列问题的测试。结果表明,可以在几秒钟内获得高质量的计划。

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