Paper Info
Title
Personalized queues: the customer view, via a fluid model of serving least-patient first.
Abstract
In personalized queues, information at the level of individuals—customers or servers—affects system dynamics. Such information is becoming increasingly accessible, directly or statistically, as exemplified by personalized/precision medicine (customers) or call center workforce management (servers). In the present work, we take advantage of personalized information about , specifically knowledge of their actual (im)patience while waiting to be served. This waiting takes place in a many-server queue that alternates between over- and underloaded periods, hence a fluid view provides a natural modeling framework. The parsimonious fluid view enables us to parameterize and analyze information, and consequently calculate and understand the benefits from personalized customer information. We do this by comparing least-patience first (LPF) routing (personalized) against FCFS (relatively info-ignorant). An example of a resulting insight is that LPF can provide significant advantages over FCFS when the durations of overloaded periods are comparable to (im)patience times.
Year
DOI
Venue
2017
https://doi.org/10.1007/s11134-017-9537-y
Queueing Syst.
Keywords
Field
DocType
Multi-server queue,Time-varying queue,Fluid approximation/model,Earliest deadline first,60K25,90B22
Patience,Precision medicine,Computer science,Customer information,Server,Queue,Real-time computing,System dynamics,Earliest deadline first scheduling,Workforce management
Journal
Volume
Issue
ISSN
87
1-2
0257-0130
Citations 
PageRank 
References 
0
0.34
15
Authors
2
Name
Order
Citations
PageRank
Avishai Mandelbaum1106185.79
Petar Momcilovic29312.28