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. © 2009 Springer Berlin Heidelberg.
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CITATION STYLE
Auger, A., Hansen, N., Perez Zerpa, J. M., Ros, R., & Schoenauer, M. (2009). Experimental comparisons of derivative free optimization algorithms (invited talk). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5526 LNCS, pp. 3–15). https://doi.org/10.1007/978-3-642-02011-7_3
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