Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/74343
Title: Capacity allocation in a service system : parametric and data-driven approaches
Authors: Liang, L
Xiao, G
Ye, H 
Keywords: Effective bandwidth
Queueing
Sample average approximation
Issue Date: 2017
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2017, v. 10286, p. 295-307 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: We study the capacity allocation problem for a service system that serves its customers with a deterministic service time under a service level requirement. The service level is measured by the probability of customers waiting longer than a pre-specified duration. We model the system as an M/D/1 or a G/D/1 queue and examine two approaches to determining the capacity: a parametric approach based on the effective bandwidth theory and a data-driven approach based on the sample average approximation. We conduct a numerical study to investigate the effectiveness of these two approaches, and find that the data-driven approach is more streamlined, accurate, and widely applicable.
Description: 8th International Conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics, and Risk Management, DHM 2017, held as part of 19th International Conference on Human-Computer Interaction, HCI 2017, 9 - 14 July 2017
URI: http://hdl.handle.net/10397/74343
ISBN: 9783319584621
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-319-58463-8_25
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