HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Journal articles

A Multiobjective Methodology for Evaluating Genetic Operators

Abstract : This paper is concerned with the problem of evaluating genetic algorithm (GA) operator combinations. Each GA operator, like crossover or mutation, can be implemented according to several different formulations. This paper shows that: 1) the performances of different operators are not dependent and 2) different merit figures for measuring a GA performance are conflicting. In order to account for this problem structure, a multiobjective analysis methodology is proposed. This methodology is employed for the evaluation of a new crossover operator (real-biased crossover) that is shown to bring a performance enhancement. A GA that was found by the proposed methodology is applied in an electromagnetic (EM) benchmark problem.
Complete list of metadata

Cited literature [13 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-00082764
Contributor : Publications Ampère Connect in order to contact the contributor
Submitted on : Tuesday, October 31, 2006 - 5:07:23 PM
Last modification on : Tuesday, March 30, 2021 - 4:20:04 PM
Long-term archiving on: : Monday, April 5, 2010 - 11:33:09 PM

Identifiers

Citation

Ricardo Takahashi, Joao Vasconcelos, Jaime Ramirez, Laurent Krähenbühl. A Multiobjective Methodology for Evaluating Genetic Operators. IEEE Transactions on Magnetics, Institute of Electrical and Electronics Engineers, 2003, 39 (3), pp.1321-1324. ⟨10.1109/TMAG.2003.810371⟩. ⟨hal-00082764⟩

Share

Metrics

Record views

366

Files downloads

134