Experimental Comparisons of Derivative Free Optimization Algorithms
Numerical Analysis
2010-06-01 v1
Abstract
In this paper, the performances of the quasi-Newton BFGS algorithm, the NEWUOA derivative free optimizer, the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), the Differential Evolution (DE) algorithm and Particle Swarm Optimizers (PSO) are compared experimentally on benchmark functions reflecting important challenges encountered in real-world optimization problems. Dependence of the performances in the conditioning of the problem and rotational invariance of the algorithms are in particular investigated.
Cite
@article{arxiv.1005.5631,
title = {Experimental Comparisons of Derivative Free Optimization Algorithms},
author = {Anne Auger and Nikolaus Hansen and Jorge M. Perez Zerpa and Raymond Ros and Marc Schoenauer},
journal= {arXiv preprint arXiv:1005.5631},
year = {2010}
}
Comments
8th International Symposium on Experimental Algorithms, Dortmund : Germany (2009)