Please use this identifier to cite or link to this item:
Title: Hybrid evolutionary algorithm with Hermite radial basis function interpolants for computationally expensive adjoint solvers
Authors: Ong, Y.S.
Lum, K.Y. 
Nair, P.B.
Keywords: Computationally expensive adjoint solver
Gradient-based approximation
Hermite radial basis function
Hybrid evolutionary algorithm
Issue Date: Jan-2008
Citation: Ong, Y.S., Lum, K.Y., Nair, P.B. (2008-01). Hybrid evolutionary algorithm with Hermite radial basis function interpolants for computationally expensive adjoint solvers. Computational Optimization and Applications 39 (1) : 97-119. ScholarBank@NUS Repository.
Abstract: In this paper, we present an evolutionary algorithm hybridized with a gradient-based optimization technique in the spirit of Lamarckian learning for efficient design optimization. In order to expedite gradient search, we employ local surrogate models that approximate the outputs of a computationally expensive Euler solver. Our focus is on the case when an adjoint Euler solver is available for efficiently computing the sensitivities of the outputs with respect to the design variables. We propose the idea of using Hermite interpolation to construct gradient-enhanced radial basis function networks that incorporate sensitivity data provided by the adjoint Euler solver. Further, we conduct local search using a trust-region framework that interleaves gradient-enhanced surrogate models with the computationally expensive adjoint Euler solver. This ensures that the present hybrid evolutionary algorithm inherits the convergence properties of the classical trust-region approach. We present numerical results for airfoil aerodynamic design optimization problems to show that the proposed algorithm converges to good designs on a limited computational budget. © 2007 Springer Science+Business Media, LLC.
Source Title: Computational Optimization and Applications
ISSN: 09266003
DOI: 10.1007/s10589-007-9065-5
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Oct 19, 2021


checked on Oct 19, 2021

Page view(s)

checked on Oct 14, 2021

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.