Input uncertainty quantification for simulation models with piecewise-constant non-stationary poisson arrival processes

Lucy E. Morgan, Andrew C. Titman, David J. Worthington, Barry L. Nelson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

Input uncertainty (IU) is the outcome of driving simulation models using input distributions estimated by finite amounts of real-world data. Methods have been presented for quantifying IU when stationary input distributions are used. In this paper we extend upon this work and provide two methods for quantifying IU in simulation models driven by piecewise-constant non-stationary Poisson arrival processes. Numerical evaluation and illustrations of the methods are provided and indicate that the methods perform well.

Original languageEnglish (US)
Title of host publication2016 Winter Simulation Conference
Subtitle of host publicationSimulating Complex Service Systems, WSC 2016
EditorsTheresa M. Roeder, Peter I. Frazier, Robert Szechtman, Enlu Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages370-381
Number of pages12
ISBN (Electronic)9781509044863
DOIs
StatePublished - Jul 2 2016
Event2016 Winter Simulation Conference, WSC 2016 - Arlington, United States
Duration: Dec 11 2016Dec 14 2016

Publication series

NameProceedings - Winter Simulation Conference
Volume0
ISSN (Print)0891-7736

Other

Other2016 Winter Simulation Conference, WSC 2016
Country/TerritoryUnited States
CityArlington
Period12/11/1612/14/16

Funding

We gratefully acknowledge the support of the EPSRC funded EP/L015692/1 STOR-i Centre for Doctoral Training, NSF Grant CMMI-1068473 and GOALI sponsor Simio LLC.

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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