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

Liping LIANG, Guanlian XIAO, Hengqing YE

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

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 languageEnglish
Title of host publicationDigital 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
PublisherSpringer-Verlag GmbH and Co. KG
Pages295-307
Number of pages13
DOIs
Publication statusPublished - 1 Jan 2017

Bibliographical note

Paper presented at the 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, Vancouver, British Columbia, Canada. ISBN of the source publication: 9783319584621

Keywords

  • Effective bandwidth
  • Queueing
  • Sample average approximation

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