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Intelligent Gradient-Based Search of Incompletely Defined Design Spaces

Published

Author(s)

Mark Schwabacher, A Gelsey

Abstract

Gradient-based numerical optimization of complex engineering designs o ers the promise of rapidly producing better designs. However, such methods generally assume that the objective function and constraint functions are continuous, smooth, and de- ned everywhere. Unfortunately, realistic simulators tend to violate these assumptions. We present a rule-based technique for intelligently computing gradients in the presence of such pathologies in the simulators, and show how this gradient computation method can be used as part of a gradient-based numerical optimization system. We tested the resulting system in the domain of conceptual design of supersonic transport aircraft, and found that using rule-based gradients can decrease the cost of design space search by one or more orders of magnitude
Citation
Artificial Intelligence in Engineering
Volume
11:3

Keywords

gradients, Optimization, rule-based systems, sequential quadratic programming

Citation

Schwabacher, M. and Gelsey, A. (1997), Intelligent Gradient-Based Search of Incompletely Defined Design Spaces, Artificial Intelligence in Engineering, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822343 (Accessed May 26, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created January 1, 1997, Updated February 19, 2017