Capacity allocation in a service system : parametric and data-driven approaches

L. Liang; G. Xiao; H. Ye

doi:10.1007/978-3-319-58463-8_25

Capacity allocation in a service system : parametric and data-driven approaches

L. Liang, G. Xiao, H. Ye

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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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.

Original language	English
Title of host publication	Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management: Ergonomics and Design : 8th International Conference, DHM 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part I
Editors	Vincent G. Duffy
Place of Publication	Dordrecht
Publisher	Springer
Pages	295-307
Number of pages	13
ISBN (Electronic)	978-3-319-58463-8
ISBN (Print)	978-3-319-58462-1
DOIs	https://doi.org/10.1007/978-3-319-58463-8_25
Publication status	Published - 2017
Externally published	Yes
Event	8th International Conference on Digital Human Modeling.and Applications in Health, Safety, Ergonomics, and Risk Management (DHM 2017) - Vancouver, Canada Duration: 9 Jul 2017 → 14 Jul 2017 http://2017.hci.international/dhm

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10286 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Exhibition

Exhibition	8th International Conference on Digital Human Modeling.and Applications in Health, Safety, Ergonomics, and Risk Management (DHM 2017)
Abbreviated title	DHM 2017
Country/Territory	Canada
City	Vancouver
Period	9/07/17 → 14/07/17
Other	Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017
Internet address	http://2017.hci.international/dhm

Keywords

Effective bandwidth
Queueing
Sample average approximation

Access to Document

10.1007/978-3-319-58463-8_25

Cite this

Liang, L., Xiao, G., & Ye, H. (2017). Capacity allocation in a service system : parametric and data-driven approaches. In V. G. Duffy (Ed.), Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management: Ergonomics and Design : 8th International Conference, DHM 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part I (pp. 295-307). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10286 LNCS). Springer. https://doi.org/10.1007/978-3-319-58463-8_25

Liang, L. ; Xiao, G. ; Ye, H. / Capacity allocation in a service system : parametric and data-driven approaches. Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management: Ergonomics and Design : 8th International Conference, DHM 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part I . editor / Vincent G. Duffy. Dordrecht : Springer, 2017. pp. 295-307 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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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.",

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Liang, L, Xiao, G & Ye, H 2017, Capacity allocation in a service system : parametric and data-driven approaches. in VG Duffy (ed.), Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management: Ergonomics and Design : 8th International Conference, DHM 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part I . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10286 LNCS, Springer, Dordrecht, pp. 295-307, 8th International Conference on Digital Human Modeling.and Applications in Health, Safety, Ergonomics, and Risk Management (DHM 2017), Vancouver, British Columbia, Canada, 9/07/17. https://doi.org/10.1007/978-3-319-58463-8_25

Capacity allocation in a service system : parametric and data-driven approaches. / Liang, L.; Xiao, G.; Ye, H.
Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management: Ergonomics and Design : 8th International Conference, DHM 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part I . ed. / Vincent G. Duffy. Dordrecht: Springer, 2017. p. 295-307 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10286 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AB - 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.

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Liang L, Xiao G, Ye H. Capacity allocation in a service system : parametric and data-driven approaches. In Duffy VG, editor, Digital Human Modeling. Applications in Health, Safety, Ergonomics, and Risk Management: Ergonomics and Design : 8th International Conference, DHM 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part I . Dordrecht: Springer. 2017. p. 295-307. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-58463-8_25

Capacity allocation in a service system : parametric and data-driven approaches

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Keywords

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