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Sequential design strategies for mean response surface metamodeling via stochastic kriging with adaptive exploration and exploitation

Stochastic kriging (SK) methodology has been known as an effective metamodeling tool for approximating a mean response surface implied by a stochastic simulation. In this paper we provide some theoretical results on the predictive performance of SK, in light of which novel integrated mean squared error-based sequential design strategies are proposed to apply SIC for mean response surface metamodeling with a fixed simulation budget. Through numerical examples of different features, we show that SIC with the proposed strategies applied holds great promise for achieving high predictive accuracy by striking a good balance between exploration and exploitation. Published by Elsevier B.V.

Identiferoai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/626021
Date10 1900
CreatorsChen, Xi, Zhou, Qiang
ContributorsUniv Arizona, Dept Syst & Ind Engn
PublisherELSEVIER SCIENCE BV
Source SetsUniversity of Arizona
LanguageEnglish
Detected LanguageEnglish
TypeArticle
RightsPublished by Elsevier B.V.
Relationhttp://linkinghub.elsevier.com/retrieve/pii/S0377221717302643

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