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dc.date.accessioned 2004-05-06T19:30:54Z
dc.date.available 2004-05-06T03:00:00Z
dc.date.issued 2000
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/9386
dc.description.abstract Our interest is to define evolutionary algorithms to solve Constraint Satisfaction Problems (CSP), which indlude benefits of taditional resolution methods of CSPs as well as inherent characteristics of these kind of problems. In this paper we propose a criterion to be able to evaluate the perfomance of genetic operators within evolutionary algorithms that solve CSp. en
dc.language en es
dc.subject Algorithms es
dc.subject evolutionary algorithms; constraint satisfaction; specialized genetics operators en
dc.subject Optimization es
dc.title A criteria to select genetic operators for solving CSP en
dc.type Articulo es
sedici.identifier.uri http://journal.info.unlp.edu.ar/wp-content/uploads/2015/papers_02/acriteria.pdf es
sedici.identifier.issn 1666-6038 es
sedici.creator.person Riff Rojas, María Cristina es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Facultad de Informática es
sedici.subtype Articulo es
sedici.rights.license Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
sedici.rights.uri http://creativecommons.org/licenses/by-nc/3.0/
sedici.description.peerReview peer-review es
sedici2003.identifier ARG-UNLP-ART-0000000231 es
sedici.relation.journalTitle Journal of Computer Science & Technology es
sedici.relation.journalVolumeAndIssue vol. 1, no. 2 es


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Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)