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MULTIVARIATE HERMITE APPROXIMATION FOR DESIGN OPTIMIZATION
Author(s) -
WANG L.,
GRANDHI R. V.,
CANFIELD R. A.
Publication year - 1996
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/(sici)1097-0207(19960315)39:5<787::aid-nme881>3.0.co;2-5
Subject(s) - mathematical optimization , hermite interpolation , interpolation (computer graphics) , function approximation , context (archaeology) , multidisciplinary design optimization , mathematics , multivariate statistics , linear approximation , optimization problem , computer science , algorithm , hermite polynomials , artificial intelligence , machine learning , multidisciplinary approach , mathematical analysis , motion (physics) , paleontology , social science , physics , nonlinear system , quantum mechanics , sociology , artificial neural network , biology
An approximation based on multiple function and gradient information is developed using Hermite interpolation concepts. The goal is to build a high‐quality approximation for complex and multidisciplinary design optimization problems employing analysis such as aeroservoelasticity, structural control, probability, etc. The proposed multidimensional approximation utilizes exact analyses data generated during the course of iterative optimization. The approximation possesses the property of reproducing the function and gradient information of known data points. The accuracy of the new approach is compared with linear, reciprocal and other standard approximations. Because the proposed algorithm uses more data points, its efficiency has to be compared in the context of iterative optimization.