TY - GEN
T1 - A comparative analysis of FSS with CMA-ES and S-PSO in ill-conditioned problems
AU - Anthony, Anthony J.
AU - Lima-Neto, Fernando B.
AU - Fages, François
AU - Bastos-Filho, Carmelo J.A.
PY - 2012/8/20
Y1 - 2012/8/20
N2 - This paper presents a comparative analyzes between three search algorithms, named Fish School Search, Particle Swarm Optimization and Covariance Matrix Adaptation Evolution Strategy applied to ill-conditioned problems. We aim to demonstrate the effectiveness of the Fish School Search in the optimization processes when the objective function has ill-conditioned properties. We achieved good results for the Fish School Search and in some cases we obtained superior results when compared to the other algorithms.
AB - This paper presents a comparative analyzes between three search algorithms, named Fish School Search, Particle Swarm Optimization and Covariance Matrix Adaptation Evolution Strategy applied to ill-conditioned problems. We aim to demonstrate the effectiveness of the Fish School Search in the optimization processes when the objective function has ill-conditioned properties. We achieved good results for the Fish School Search and in some cases we obtained superior results when compared to the other algorithms.
KW - Covariance matrix adaptation
KW - Fish School Search
KW - Ill-conditioned problems
KW - Invariance
KW - Non-separable problems
KW - Particle Swarm Optimization
U2 - 10.1007/978-3-642-32639-4_51
DO - 10.1007/978-3-642-32639-4_51
M3 - Conference contribution
AN - SCOPUS:84865016280
SN - 9783642326387
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 416
EP - 422
BT - Intelligent Data Engineering and Automated Learning, IDEAL 2012 - 13th International Conference, Proceedings
T2 - 13th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2012
Y2 - 29 August 2012 through 31 August 2012
ER -