Input-output uncertainty comparisons for optimization via simulation

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

1 Scopus citations


When an optimization via simulation (OvS) procedure designed for known input distributions is applied to a problem with input uncertainty (IU), it typically does not provide the target statistical guarantee. In this paper, we focus on a discrete OvS problem where all systems share the same input distribution estimated from the common input data (CID). We define the CID effect as the joint impact of IU on the outputs of the systems caused by common input distributions. Our input-output uncertainty comparison (IOU-C) procedure leverages the CID effect to provide the joint confidence intervals (CIs) for the difference between each system's mean performance and the best of the rest incorporating both input and output uncertainty. Under mild conditions, IOU comparisons provide the target statistical guarantee as the input sample size and the simulation effort increase.

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.
Number of pages2
ISBN (Electronic)9781509044863
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
ISSN (Print)0891-7736


Other2016 Winter Simulation Conference, WSC 2016
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Software
  • Modeling and Simulation
  • Computer Science Applications


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