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Intelligent gradient-based search of incompletely defined design spaces

Published online by Cambridge University Press:  27 February 2009

Mark Schwabacher  and
Andrew Gelsey
Mark Schwabacher
Affiliation:
National Institute of Standards and Technology, Building 304, Room 12, Gaithersburg, MD 20899, U.S.A.
Andrew Gelsey
Affiliation:
Rutgers, the State University of New Jersey, New Brunswick, NJ 08903, U.S.A.
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Abstract

Gradient-based numerical optimization of complex engineering designs offers the promise of rapidly producing better designs. However, such methods generally assume that the objective function and constraint functions are continuous, smooth, and defined 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.

Keywords

OptimizationGradientsSequential Quadratic ProgrammingRule-based Systems
Type
Articles
Information
AI EDAM , Volume 11 , Issue 3 , June 1997 , pp. 199 - 210
Copyright
Copyright © Cambridge University Press 1997

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