Generating sequential space-filling designs using genetic algorithms and Monte Carlo methods
- Author
- Karel Crombecq and Tom Dhaene (UGent)
- Organization
- Abstract
- In this paper, the authors compare a Monte Carlo method and an optimization-based approach using genetic algorithms for sequentially generating space-filling experimental designs. It is shown that Monte Carlo methods perform better than genetic algorithms for this specific problem.
- Keywords
- sequential design, Monte Carlo, surrogate modelling, active learning, genetic algorithm, space-filling
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-1140796
- MLA
- Crombecq, Karel, and Tom Dhaene. “Generating Sequential Space-Filling Designs Using Genetic Algorithms and Monte Carlo Methods.” LECTURE NOTES IN COMPUTER SCIENCE, edited by K Deb et al., vol. 6457, Springer, 2010, pp. 80–84, doi:10.1007/978-3-642-17298-4_8.
- APA
- Crombecq, K., & Dhaene, T. (2010). Generating sequential space-filling designs using genetic algorithms and Monte Carlo methods. In K. Deb, A. Bhattacharya, N. Chakraborti, P. Chakroborty, S. Das, J. Dutta, … K. Tan (Eds.), LECTURE NOTES IN COMPUTER SCIENCE (Vol. 6457, pp. 80–84). https://doi.org/10.1007/978-3-642-17298-4_8
- Chicago author-date
- Crombecq, Karel, and Tom Dhaene. 2010. “Generating Sequential Space-Filling Designs Using Genetic Algorithms and Monte Carlo Methods.” In LECTURE NOTES IN COMPUTER SCIENCE, edited by K Deb, A Bhattacharya, N Chakraborti, P Chakroborty, S Das, J Dutta, SK Gupta, et al., 6457:80–84. Berlin, Germany: Springer. https://doi.org/10.1007/978-3-642-17298-4_8.
- Chicago author-date (all authors)
- Crombecq, Karel, and Tom Dhaene. 2010. “Generating Sequential Space-Filling Designs Using Genetic Algorithms and Monte Carlo Methods.” In LECTURE NOTES IN COMPUTER SCIENCE, ed by. K Deb, A Bhattacharya, N Chakraborti, P Chakroborty, S Das, J Dutta, SK Gupta, A Jain, V Aggarwal, J Branke, SJ Louis, and KC Tan, 6457:80–84. Berlin, Germany: Springer. doi:10.1007/978-3-642-17298-4_8.
- Vancouver
- 1.Crombecq K, Dhaene T. Generating sequential space-filling designs using genetic algorithms and Monte Carlo methods. In: Deb K, Bhattacharya A, Chakraborti N, Chakroborty P, Das S, Dutta J, et al., editors. LECTURE NOTES IN COMPUTER SCIENCE. Berlin, Germany: Springer; 2010. p. 80–4.
- IEEE
- [1]K. Crombecq and T. Dhaene, “Generating sequential space-filling designs using genetic algorithms and Monte Carlo methods,” in LECTURE NOTES IN COMPUTER SCIENCE, Kanpur, India, 2010, vol. 6457, pp. 80–84.
@inproceedings{1140796,
abstract = {{In this paper, the authors compare a Monte Carlo method and an optimization-based approach using genetic algorithms for sequentially generating space-filling experimental designs. It is shown that Monte Carlo methods perform better than genetic algorithms for this specific problem.}},
author = {{Crombecq, Karel and Dhaene, Tom}},
booktitle = {{LECTURE NOTES IN COMPUTER SCIENCE}},
editor = {{Deb, K and Bhattacharya, A and Chakraborti, N and Chakroborty, P and Das, S and Dutta, J and Gupta, SK and Jain, A and Aggarwal, V and Branke, J and Louis, SJ and Tan, KC}},
isbn = {{9783642172977}},
issn = {{0302-9743}},
keywords = {{sequential design,Monte Carlo,surrogate modelling,active learning,genetic algorithm,space-filling}},
language = {{eng}},
location = {{Kanpur, India}},
pages = {{80--84}},
publisher = {{Springer}},
title = {{Generating sequential space-filling designs using genetic algorithms and Monte Carlo methods}},
url = {{http://doi.org/10.1007/978-3-642-17298-4_8}},
volume = {{6457}},
year = {{2010}},
}
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