On the approximation of empirical data for service system simulations

A Finlayson
Additional contact information
A Finlayson: Teesside University Business School, Tees Valley, UK

Journal of the Operational Research Society, 2013, vol. 64, issue 7, 1021-1029

Abstract: The difficulties associated with parameter estimation for phase-type approximations of empirical data distributions in queue modelling are well known. While significant progress has been achieved in improving such approximations, difficulties in parameter estimation still limit the extent to which queue modelling is applied in practice. This paper presents a simplified technique for approximating empirical data in service system simulations, based on the specialised Cox phase-type distribution. When utilised in simulation modelling of a service system, the specialised Cox distribution is shown to provide improved approximations to the combined waiting and service time distribution without the need for complex parameter estimation techniques. This approach should enable much greater flexibility in the application of queue modelling to service systems.

Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.palgrave-journals.com/jors/journal/v64/n7/pdf/jors2012127a.pdf Link to full text PDF (application/pdf)
http://www.palgrave-journals.com/jors/journal/v64/n7/full/jors2012127a.html Link to full text HTML (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:jorsoc:v:64:y:2013:i:7:p:1021-1029

Ordering information: This journal article can be ordered from
http://www.springer. ... search/journal/41274

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald and Jonathan Crook

More articles in Journal of the Operational Research Society from Palgrave Macmillan, The OR Society
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().