Sareni, Bruno and Krähenbühl, Laurent and Nicolas, Alain Efficient genetic algorithms for solving hard constrained optimization problems. (2000) IEEE Transactions on Magnetics, 36 (4). 1027-1030. ISSN 0018-9464
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(Document in English)
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Official URL: http://dx.doi.org/10.1109/20.877616
Abstract
This paper studies many Genetic Algorithm strategies to solve hard-constrained optimization problems. It investigates the role of various genetic operators to avoid premature convergence. In particular, an analysis of niching methods is carried out on a simple function to show advantages and drawbacks of each of them. Comparisons are also performed on an original benchmark based on an electrode shape optimization technique coupled with a charge simulation method
| Item Type: | Article |
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| Additional Information: | Thanks to IEEE editor. The original publication is available at http://ieeexplore.ieee.org |
| Audience (journal): | International peer-reviewed journal |
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| Institution: | French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE) Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE) Other partners > Institut National des Sciences Appliquées de Lyon - INSA (FRANCE) Other partners > Université Claude Bernard-Lyon I - UCBL (FRANCE) Other partners > Ecole Centrale de Lyon (FRANCE) |
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| Statistics: | download |
| Deposited By: | Bruno SARENI |
| Deposited On: | 20 Dec 2012 09:42 |
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