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.
|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|
|Publisher||Springer-Verlag GmbH and Co. KG|
|Number of pages||13|
|Publication status||Published - 1 Jan 2017|
Bibliographical notePaper 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
- Effective bandwidth
- Sample average approximation