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ROBUST CAPACITY PLANNING FOR ACCIDENT AND EMERGENCY SERVICES

机译:意外和紧急服务的强大容量规划

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摘要

Accident and emergency departments (A&E) are the first place of contact for urgent and complex patients. These departments are subject to uncertainties due to the unplanned patient arrivals. After arrival to an A&E, patients are categorized by a triage nurse based on the urgency. The performance of an A&E is measured based on the number of patients waiting for more than a certain time to be treated. Due to the uncertainties affecting the patient flow, finding the optimum staff capacities while ensuring the performance targets is a complex problem. This paper proposes a robust-optimization based approximation for the patient waiting times in an A&E. We also develop a simulation optimization heuristic to solve this capacity planning problem. The performance of the approximation approach is then compared with that of the simulation optimization heuristic. Finally, the impact of model parameters on the performances of two approaches is investigated. The experiments show that the proposed approximation results in good enough solutions.
机译:事故和急诊部门(A&E)是紧急和复杂患者的第一个接触者。由于计划的患者抵达,这些部门受到不确定性的影响。到达A&E后,患者根据紧急性分类。 A&E的性能是基于等待待治疗的一定时间的患者的数量来测量。由于影响患者流量的不确定性,找到最佳的员工能力,同时确保性能目标是一个复杂的问题。本文提出了一种基于稳健的优化,用于A&E中的患者等待时间的近似。我们还开发了一种仿真优化启发式,解决了这个容量规划问题。然后将近似方法的性能与模拟优化启发式的性能进行比较。最后,研究了模型参数对两种方法的性能的影响。实验表明,所提出的近似导致足够好的解决方案。

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