RESEARCH PAPERS: Design Automation Papers

Approximation of Computationally Expensive and Noisy Functions for Constrained Nonlinear Optimization

[+] Author and Article Information
J. W. Free, A. R. Parkinson

Department of Mechanical Engineering, Brigham Young University, Provo, Utah 84602

G. R. Bryce

Department of Statistics, Brigham Young University, Provo, Utah 84602

R. J. Balling

Department of Civil Engineering, Brigham Young University, Provo, Utah 84602

J. Mech., Trans., and Automation 109(4), 528-532 (Dec 01, 1987) (5 pages) doi:10.1115/1.3258832 History: Received April 09, 1987; Online November 19, 2009


The use of statistical experimental designs is explored as a method of approximating computationally expensive and noisy functions. The advantages of experimental designs and function approximation for use in optimization are discussed. Several test problems are reported showing the approximation method to be competitive with the most efficient optimization algorithms when no noise is present. When noise is introduced, the approximation method is more efficient and solves more problems than conventional nonlinear programming algorithms.

Copyright © 1987 by ASME
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