Work

Experimental Comparisons of Derivative Free Optimization Algorithms

Year: 2010

Type: preprint

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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1005.5631

Authors: Auger, Anne, Hansen, Nikolaus, Zerpa, Jorge M. Perez, Ros, Raymond, Schoenauer, Marc

Institutions: Institut national de recherche en sciences et technologies du numérique, Centre Inria de Saclay

Language: English

Topic: Metaheuristic Optimization Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2950180853

Cites: 12

Cited by: 1

Related to: 20