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Discrete-Event Simulation and Integer Linear Programming for Constraint-Aware Resource Scheduling

机译:约束感知资源调度的离散事件仿真和整数线性规划

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摘要

This paper presents a method for scheduling resources in complex systems that integrate humans with diverse hardware and software components, and for studying the impact of resource schedules on system characteristics. The method uses discrete-event simulation and integer linear programming, and relies on detailed models of the system’s processes, specifications of the capabilities of the system’s resources, and constraints on the operations of the system and its resources. As a case study, we examine processes involved in the operation of a hospital emergency department, studying the impact staffing policies have on such key quality measures as patient length of stay (LoS), number of handoffs, staff utilization levels, and cost. Our results suggest that physician and nurse utilization levels for clinical tasks of 70% result in a good balance between LoS and cost. Allowing shift lengths to vary and shifts to overlap increases scheduling flexibility. Clinical experts provided face validation of our results. Our approach improves on the state of the art by enabling using detailed resource and constraint specifications effectively to support analysis and decision making about complex processes in domains that currently rely largely on trial and error and other ad hoc methods.
机译:本文提出了一种在复杂系统中调度资源的方法,该系统将人与各种硬件和软件组件集成在一起,并研究了资源调度对系统特性的影响。该方法使用离散事件模拟和整数线性规划,并且依赖于系统过程的详细模型,系统资源功能的规格以及对系统及其资源操作的约束。作为案例研究,我们检查了医院急诊科运作中涉及的流程,研究人员配备政策对关键质量指标的影响,例如患者的住院时间(LoS),移交次数,人员利用率水平和成本。我们的结果表明,医师和护士对临床任务的利用率为70%,可以在视距和成本之间取得良好的平衡。允许轮班长度变化和轮班重叠以增加调度灵活性。临床专家对我们的结果进行了面部验证。我们的方法通过有效地使用详细的资源和约束规范来支持有关领域中当前主要依赖试验和错误以及其他临时方法的复杂过程的分析和决策,从而改进了现有技术。

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