PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Experimental Comparisons of Derivative Free Optimization Algorithms
Anne Auger, Nikolaus Hansen, Jorge Perez Zerpa, Raymond Ros and Marc Schoenauer
In: 8th International Symposium on Experimental Algorithms LNCS (5526). (2009) Springer Verlag , pp. 3-15. ISBN 978-3-642-02010-0

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.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:6907
Deposited By:Marc Schoenauer
Deposited On:13 April 2010