Experimental Comparisons of Derivative Free Optimization Algorithms

Anne Auger 1, 2 Nikolaus Hansen 2 Jorge Perez Zerpa 1 Raymond Ros 1 Marc Schoenauer 1, 2
1 TAO - Machine Learning and Optimisation
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
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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Conference papers
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https://hal.inria.fr/inria-00397334
Contributor : Marc Schoenauer <>
Submitted on : Thursday, June 25, 2009 - 4:37:09 PM
Last modification on : Monday, December 9, 2019 - 5:24:06 PM
Long-term archiving on: Saturday, November 26, 2016 - 9:47:57 AM

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Anne Auger, Nikolaus Hansen, Jorge Perez Zerpa, Raymond Ros, Marc Schoenauer. Experimental Comparisons of Derivative Free Optimization Algorithms. 8th International Symposium on Experimental Algorithms, Jun 2009, Dortmund, Germany. ⟨inria-00397334v2⟩

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