CONDOR, a new parallel, constrained extension of Powell's UOBYQA
algorithm: Experimental results and comparison with the DFO algorithm
F. Berghen, and H. Bersini. Journal of Computational and Applied Mathematics, 181 (1):
157-175(September 2005)
Abstract
This paper presents an algorithmic extension of Powell's UOBYQA algorithm
(Unconstrained Optimization BY Quadratical Approximation). We start
by summarizing the original algorithm of Powell and by presenting
it in a more comprehensible form. Thereafter, we report comparative
numerical results between UOBYQA, DFO and a parallel, constrained
extension of UOBYQA that will be called in the paper CONDOR (COnstrained,
Non-linear, Direct, parallel Optimization using trust Region method
for high-computing load function). The experimental results are very
encouraging and validate the approach. They open wide possibilities
in the field of noisy and high-computing-load objective functions
optimization (from 2 min to several days) like, for instance, industrial
shape optimization based on computation fluid dynamic codes or partial
differential equations solvers. Finally, we present a new, easily
comprehensible and fully stand-alone implementation in C++ of the
parallel algorithm. (c) 2004 Elsevier B.V. All rights reserved.
%0 Journal Article
%1 Vanden2005
%A Berghen, F. Vanden
%A Bersini, H.
%D 2005
%J Journal of Computational and Applied Mathematics
%K INTERPOLATION Lagrange OPTIMIZATION; computing design; high-computing-load; interpolation; method; noisy nonlinear; optimal optimization; parallel region shape trust
%N 1
%P 157-175
%T CONDOR, a new parallel, constrained extension of Powell's UOBYQA
algorithm: Experimental results and comparison with the DFO algorithm
%U <Go to ISI>://000229805500011
%V 181
%X This paper presents an algorithmic extension of Powell's UOBYQA algorithm
(Unconstrained Optimization BY Quadratical Approximation). We start
by summarizing the original algorithm of Powell and by presenting
it in a more comprehensible form. Thereafter, we report comparative
numerical results between UOBYQA, DFO and a parallel, constrained
extension of UOBYQA that will be called in the paper CONDOR (COnstrained,
Non-linear, Direct, parallel Optimization using trust Region method
for high-computing load function). The experimental results are very
encouraging and validate the approach. They open wide possibilities
in the field of noisy and high-computing-load objective functions
optimization (from 2 min to several days) like, for instance, industrial
shape optimization based on computation fluid dynamic codes or partial
differential equations solvers. Finally, we present a new, easily
comprehensible and fully stand-alone implementation in C++ of the
parallel algorithm. (c) 2004 Elsevier B.V. All rights reserved.
@article{Vanden2005,
abstract = {This paper presents an algorithmic extension of Powell's UOBYQA algorithm
(Unconstrained Optimization BY Quadratical Approximation). We start
by summarizing the original algorithm of Powell and by presenting
it in a more comprehensible form. Thereafter, we report comparative
numerical results between UOBYQA, DFO and a parallel, constrained
extension of UOBYQA that will be called in the paper CONDOR (COnstrained,
Non-linear, Direct, parallel Optimization using trust Region method
for high-computing load function). The experimental results are very
encouraging and validate the approach. They open wide possibilities
in the field of noisy and high-computing-load objective functions
optimization (from 2 min to several days) like, for instance, industrial
shape optimization based on computation fluid dynamic codes or partial
differential equations solvers. Finally, we present a new, easily
comprehensible and fully stand-alone implementation in C++ of the
parallel algorithm. (c) 2004 Elsevier B.V. All rights reserved.},
added-at = {2007-11-22T09:11:49.000+0100},
author = {Berghen, F. Vanden and Bersini, H.},
biburl = {https://www.bibsonomy.org/bibtex/21f235f4f8a74840ebeb598e67b10cc12/tboehme},
endnotereftype = {Journal Article},
interhash = {5ff19083917be6e6a5af7c5fd1984af8},
intrahash = {1f235f4f8a74840ebeb598e67b10cc12},
journal = {Journal of Computational and Applied Mathematics},
keywords = {INTERPOLATION Lagrange OPTIMIZATION; computing design; high-computing-load; interpolation; method; noisy nonlinear; optimal optimization; parallel region shape trust},
month = Sep,
number = 1,
pages = {157-175},
shorttitle = {CONDOR, a new parallel, constrained extension of Powell's UOBYQA algorithm:
Experimental results and comparison with the DFO algorithm},
timestamp = {2007-11-22T09:12:07.000+0100},
title = {CONDOR, a new parallel, constrained extension of Powell's UOBYQA
algorithm: Experimental results and comparison with the DFO algorithm},
url = {<Go to ISI>://000229805500011 },
volume = 181,
year = 2005
}