CONDOR, a new parallel, constrained extension of Powell's UOBYQA algorithm: Experimental results and comparison with the DFO algorithm

作者:

Highlights:

摘要

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.

论文关键词:Nonlinear,High-computing-load,Noisy optimization,Lagrange interpolation,Trust region method,Optimal shape design,Parallel computing

论文评审过程:Received 8 November 2004, Available online 7 January 2005.

论文官网地址:https://doi.org/10.1016/j.cam.2004.11.029