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dc.date.accessioned 2012-11-28T17:58:28Z
dc.date.available 2012-11-28T17:58:28Z
dc.date.issued 1998-11
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/24821
dc.description.abstract Multiple crossover per couple (MCPC) is a newly introduced crossover method which in contrast with the single crossover per couple approach (SCPC), permits more than one crossover operation for each mating pair. MCPC was applied to optimise classic testing functions and some harder (non-linear, non-separable) functions. The goodness of this approach prevailed under all tests and revealed that, when MCPC is applied with 2, 3 and 4 crossovers per couple, results as good as under SCPC can be expected with an additional benefit in processing time. This performance was obtained through the ability showed by MCPC of exploiting the recombination of good, formerly found solutions. But on the other hand, those experiments also showed that, in some cases, the method increased the risk of premature convergence due to a loss of genetic diversity. This paper gives an insight of the convenience of binding the choice of a selection mechanism to the genetic operators used. Focussing on this problem experiments with MCPC under proportional, and ranking selection methods were performed. In the case of ranking, an adaptive approach was carried out to adjust selective pressure. Descriptions of the alternative selection mechanisms used, experiments and some of the results obtained under each method are shown. en
dc.language en es
dc.subject Biology and genetics es
dc.subject genetic algorithms en
dc.subject Algorithms es
dc.subject selections mechanism en
dc.subject Combinatorial algorithms es
dc.subject crossover en
dc.subject Selection process es
dc.subject function optimization en
dc.title A study of alternative selection mechanisms for multiple cossover per couple in genetic algorithms en
dc.type Objeto de conferencia es
sedici.creator.person Esquivel, Susana Cecilia es
sedici.creator.person Leiva, Héctor Ariel es
sedici.creator.person Gallard, Raúl Hector es
sedici.description.note Sistemas Inteligentes es
sedici.subject.materias Ciencias Informáticas es
sedici.subject.materias Informática es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 1998-10
sedici.relation.event IV Congreso Argentina de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)