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

Xi Chen, Qiang Zhou

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

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 SK for mean response surface metamodeling with a fixed simulation budget. Through numerical examples of different features, we show that SK with the proposed strategies applied holds great promise for achieving high predictive accuracy by striking a good balance between exploration and exploitation.

Original languageEnglish (US)
Pages (from-to)575-585
Number of pages11
JournalEuropean Journal of Operational Research
Volume262
Issue number2
DOIs
StatePublished - Oct 16 2017

Keywords

  • Sequential experimental design
  • Simulation
  • Simulation analysis and methodology
  • Simulation metamodeling

ASJC Scopus subject areas

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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