Robust simulation of stochastic systems with input uncertainties modeled by statistical divergences

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review

View graph of relations

Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings - Winter Simulation Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages643-654
Volume2016-February
ISBN (Print)9781467397438
StatePublished - 16 Feb 2016

Publication series

Name
Volume2016-February
ISSN (Print)0891-7736

Conference

TitleWinter Simulation Conference, WSC 2015
PlaceUnited States
CityHuntington Beach
Period6 - 9 December 2015

Abstract

Simulation is often used to study stochastic systems. A key step of this approach is to specify a distribution for the random input. This is called input modeling, which is important and even critical for simulation study. However, specifying a distribution precisely is usually difficult and even impossible in practice. This issue is called input uncertainty in simulation study. In this paper we study input uncertainty when using simulation to estimate important performance measures: expectation, probability, and value-at-risk. We propose a robust simulation (RS) approach, which assumes the real distribution is contained in a certain ambiguity set constructed using statistical divergences, and simulates the maximum and the minimum of the performance measures when the distribution varies in the ambiguity set. We show that the RS approach is computationally tractable and the corresponding results can disclose important information about the systems, which may help decision makers better understand the systems.

Citation Format(s)

Robust simulation of stochastic systems with input uncertainties modeled by statistical divergences. / Hu, Zhaolin; Hong, L. Jeff.

Proceedings - Winter Simulation Conference. Vol. 2016-February Institute of Electrical and Electronics Engineers Inc., 2016. p. 643-654 7408203.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)Not applicablepeer-review