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Mostrar registro sencillo 2012-10-22T13:41:33Z 2012-10-22T13:41:33Z 2003-10
dc.description.abstract In evolutionary algorithms based on genetics, the crossover operation creates individuals by interchanging genes. On the other side selection mechanisms aim to favour reproduction of better individuals imposing a direction on the search process: copies of better ones replace worst individuals. Consequently, part of the genetic material contained in these worst individuals disappears forever. This loss of diversity can lead to a premature convergence. To prevent a premature convergence to a local optimum under the same selection mechanism and multirecombined scheme then, either a larger population size or adequate crossover and mutation operators are needed. In this work we are showing the effect on genetic diversity, quality of results and required computational effort, when applying different crossover methods to a set of very hard instances of the weighted tardiness scheduling problem in single machine environments. For these experiments we are using multirecombined approaches which allow multiple crossover operations on multiple parent each time a new individual is generated. A description of each method, experiments and preliminary results are reported. en
dc.format.extent p. 658-669 es
dc.language en es
dc.title Influence of crossover operators in evolutionary scheduling under multirecombined schemes en
dc.type Objeto de conferencia es
sedici.creator.person San Pedro, María Eugenia de es
sedici.creator.person Pandolfi, Daniel es
sedici.creator.person Villagra, Andrea es
sedici.creator.person Lasso, Marta Graciela es
sedici.creator.person Gallard, Raúl Hector es
sedici.description.note Eje: Agentes y Sistemas Inteligentes (ASI) es
sedici.subject.materias Ciencias Informáticas es
sedici.subject.keyword Evolutionary Scheduling en
sedici.subject.keyword Weighted Tardiness en
sedici.subject.keyword Crossover Operators en
sedici.subject.keyword genetic diversity en
sedici.description.fulltext true es 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 2003-10
sedici.relation.event IX Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es
sedici.subject.acmcss98 Scheduling es
sedici.subject.acmcss98 Algorithms es
sedici.subject.acmcss98 ARTIFICIAL INTELLIGENCE es
sedici.subject.acmcss98 Intelligent agents 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)