%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 }