Relative error stochastic kriging

Authors:
Mustafa H. Tongarlak;Bruce E. Ankenman;Barry L. Nelson
Affiliations:
Northwestern University, Evanston, IL;Northwestern University, Evanston, IL;Northwestern University, Evanston, IL
Venue:
Proceedings of the Winter Simulation Conference
Year:
2011

Citing 3
Cited 0

Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)

Simulation Modeling and Analysis (McGraw-Hill Series in Industrial Engineering and Management)
Widely convergent method for finding multiple solutions of simultaneous nonlinear equations

IBM Journal of Research and Development
Stochastic Kriging for Simulation Metamodeling

Operations Research

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Abstract

We use stochastic kriging to build predictors with bounded relative error over the design space. We propose design strategies that guide sequential algorithms with and without adaptation to the data to make allocation and stopping decisions such that a prespecified relative precision is realized with some confidence. We also present an empirical evaluation of the proposed design strategies.