计算机科学
调度(生产过程)
动态优先级调度
运筹学
杠杆(统计)
医疗保健
作业车间调度
业务流程
运营管理
服务质量
人工智能
计算机网络
在制品
工程类
布线(电子设计自动化)
经济
经济增长
作者
Christos Zacharias,Nan Liu,Mehmet A. Begen
出处
期刊:Operations Research
[Institute for Operations Research and the Management Sciences]
日期:2024-01-01
卷期号:72 (1): 317-335
被引量:4
标识
DOI:10.1287/opre.2022.2342
摘要
Adaptive Patient Flow Management Appointment scheduling has significant clinical, operational, and economical impact on healthcare systems. An informed scheduling strategy that can effectively match patient demand and service capacity dynamically is vital for the business of medical providers, quality of care, and patient satisfaction. By regulating patient flow via an appointment system, healthcare providers can mitigate arrival process variability and improve operational performance. The simultaneous consideration of appointment day (interday scheduling) and time of day (intraday scheduling) in dynamic scheduling decisions is an important theoretical and practical problem that has remained open because of its stochastic nature, complex structure, and large dimensionality. Zacharias et al. (2022) fill this critical gap in the literature. They introduce a novel dynamic programming framework, designed with the intention of bridging two independently established streams of literature, and to leverage their latest advances in tackling the joint problem. They advance the theory of the field to provide a rigorous and practically implantable solution.
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