Adaptive sampling for optimization under uncertainty

Z. Wan, Takeru Igusa

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

Abstract

The problems of interest are where the objective function must be evaluated using sampling techniques. The sampled function values are used to build an approximation to the response surface over the product space of uncertainties and design variables. This approximation is successively used in the integration over the space of uncertainties and in the optimization (minimization) over the space of design variables. A surrogate-based trust region method is used to determine a succession of design points for optimization.

Original languageEnglish (US)
Title of host publication4th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2003
EditorsNii O. Attoh-Okine, Bilal M. Ayyub
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages423-428
Number of pages6
ISBN (Electronic)0769519970, 9780769519975
DOIs
Publication statusPublished - Jan 1 2003
Event4th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2003 - College Park, United States
Duration: Sep 21 2003Sep 24 2003

Other

Other4th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2003
CountryUnited States
CityCollege Park
Period9/21/039/24/03

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Keywords

  • Approximation algorithms
  • Civil engineering
  • Convergence
  • Design optimization
  • Estimation error
  • History
  • Response surface methodology
  • Sampling methods
  • Statistics
  • Uncertainty

ASJC Scopus subject areas

  • Statistics, Probability and Uncertainty
  • Control and Optimization
  • Modeling and Simulation

Cite this

Wan, Z., & Igusa, T. (2003). Adaptive sampling for optimization under uncertainty. In N. O. Attoh-Okine, & B. M. Ayyub (Eds.), 4th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2003 (pp. 423-428). [1236195] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISUMA.2003.1236195