A Comparative Study of CMA-ES on Large Scale Global Optimisation

Omidvar, M and Li, X 2010, 'A Comparative Study of CMA-ES on Large Scale Global Optimisation', in Jiuyong Li and John Debenham (ed.) Proceedings of the 23rd Australasian Joint Conference on Artificial Intelligence (AI'10), Adelaide, Australia, December 7-10, 2010, pp. 303-312.


Document type: Conference Paper
Collection: Conference Papers

Title A Comparative Study of CMA-ES on Large Scale Global Optimisation
Author(s) Omidvar, M
Li, X
Year 2010
Conference name 23rd Australasian Joint Conference on Artificial Intelligence (AI'10)
Conference location Adelaide, Australia
Conference dates December 7-10, 2010
Proceedings title Proceedings of the 23rd Australasian Joint Conference on Artificial Intelligence (AI'10)
Editor(s) Jiuyong Li and John Debenham
Publisher Springer
Place of publication Berlin, Germany
Start page 303
End page 312
Total pages 10
Abstract In this paper, we investigate the performance of CMA-ES on large scale non-separable optimisation problems. CMA-ES is a robust local optimiser that has shown great performance on small-scale nonseparable optimisation problems. Self-adaptation of a covariance matrix makes it rotational invariant which is a desirable property, especially for solving non-separable problems. The focus of this paper is to compare the performance of CMA-ES with Cooperative Co-evolutionary Algorithms (CCEAs) for large scale global optimisation (on problems with up to 1000 real-valued variables).
Subjects Pattern Recognition and Data Mining
Neural, Evolutionary and Fuzzy Computation
Optimisation
Keyword(s) Artificial Intelligence
Copyright notice © Springer-Verlag Berlin Heidelberg 2010
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