 |
 |
|
|
| HAL: hal-00135911, version 1 |
| DOI: 10.1109/20.877616 |
| Detailed view |  Export this paper |
 |
| IEEE Transactions on Magnetics 36, 4 Part 1 (2000) 1027-1030 |
|
|
|
|
| Efficient Genetic Algorithms for Solving Hard Constrained Optimization Problems |
|
|
Bruno Sareni 1, 2Laurent Krähenbühl 1, 3 |
|
|
| (2000) |
|
|
|
| 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 showadvantages 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. |
|
|
|
|
|
|
|
|
|
|
|
| 1: | Centre de génie électrique de Lyon (CEGELY) |
|
|
|
CNRS : UMR5005 – Université Claude Bernard - Lyon I – Institut National des Sciences Appliquées (INSA) - Lyon – Ecole Centrale de Lyon |
|
|
| 2: | Laboratoire électrotechnique et électronique industrielle (LEEI) |
|
|
|
CNRS : UMR5828 – Institut National Polytechnique de Toulouse - INPT |
|
|
| 3: | Ampère |
|
|
|
CNRS : UMR5005 – Université Claude Bernard - Lyon I – Institut National des Sciences Appliquées (INSA) - Lyon – Ecole Centrale de Lyon |
|
|
|
|
|
|
|
|
|
| Subject | : | Engineering Sciences/Other Engineering Sciences/Electromagnetism Mathematics/Optimization and Control |
|
|
| constrained optimization methods – genetic algorithms – niching methods – shape optimization methods |
|
|
|
| Attached file list to this document: | |||||
|
|||||
|
|
|
| hal-00135911, version 1 | |
| http://hal.archives-ouvertes.fr/hal-00135911 | |
| oai:hal.archives-ouvertes.fr:hal-00135911 | |
| From: Publications Ampère | |
| Submitted on: Tuesday, 27 March 2007 12:45:30 | |
| Updated on: Wednesday, 11 February 2009 13:22:10 | |
