A survey on skill-based routing with applications to service operations management
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A survey on skill-based routing with applications to service operations management Jinsheng Chen1 · Jing Dong2
· Pengyi Shi3
Received: 14 September 2020 / Revised: 17 September 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Service systems often feature multiple classes of customers with different service needs and multiple pools of servers with different skillsets. How to efficiently match customers of different classes with servers of different skillsets is of great importance to the management of these systems. In this survey, we review works on skill-based routing in queues. We first summarize key insights on routing/scheduling policies developed in the literature. We then discuss complications brought by modern service operations management problems, particularly healthcare systems. These complications stimulate a growing body of literature on new modeling and analysis tools. Lastly, we provide additional numerical experiments to highlight the complex nature of a routing problem motivated from hospital patient-flow management, and provide some useful intuition to develop good skill-based routing policies in practice. Our goal is to provide a brief overview of the skill-based routing research landscape and to help generate interesting research ideas. Keywords Queueing theory · Skill-based routing · Asymptotic analysis Mathematics Subject Classification 90B22
B
Jing Dong [email protected] Jinsheng Chen [email protected] Pengyi Shi [email protected]
1
Department of IEOR, Columbia University, 500 West 120th Street, New York, NY 10027, USA
2
Graduate School of Business, Columbia University, 3022 Broadway, New York, NY 10027, USA
3
Krannert School of Management, Purdue University, 403 W State St, West Lafayette, IN 47907, USA
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Queueing Systems
1 Introduction In service systems, customers are typically grouped into different classes based on their service needs. For example, in a call center, different customer types can represent different service requirements, for example, individual banking, business banking, and loans in a bank call center, or different priority levels. In a hospital inpatient department, different customer types can correspond to different medical specialties of patients, for example, general medicine, cardiology, and neurology, or different severity levels, for example, general ward, intensive care unit, and step-down unit. Correspondingly, servers (resources) are often grouped into different server pools based on their skillset/specialization to serve different types of customers. For example, call center staff are grouped into different pools based on their training or language skills, for example, English, Spanish, and bilingual. Inpatient ward beds are grouped into different specialty wards to better facilitate the coordination and standardization of care. There are several interesting design questions that arise in these service systems: (i) how to define the customer/server classes and how to design the network structure; (i
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