Influence of crossover operators in evolutionary scheduling under multirecombined schemes

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. Conse...

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Autores principales: San Pedro, María Eugenia de, Pandolfi, Daniel, Villagra, Andrea, Lasso, Marta Graciela, Gallard, Raúl Hector
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2003
Materias:
Ciencias Informáticas
Scheduling
Algorithms
ARTIFICIAL INTELLIGENCE
Intelligent agents
Evolutionary Scheduling
Weighted Tardiness
Crossover Operators
genetic diversity
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/22729
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-22729
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Scheduling
Algorithms
ARTIFICIAL INTELLIGENCE
Intelligent agents
Evolutionary Scheduling
Weighted Tardiness
Crossover Operators
genetic diversity
spellingShingle Ciencias Informáticas
Scheduling
Algorithms
ARTIFICIAL INTELLIGENCE
Intelligent agents
Evolutionary Scheduling
Weighted Tardiness
Crossover Operators
genetic diversity
San Pedro, María Eugenia de
Pandolfi, Daniel
Villagra, Andrea
Lasso, Marta Graciela
Gallard, Raúl Hector
Influence of crossover operators in evolutionary scheduling under multirecombined schemes
topic_facet Ciencias Informáticas
Scheduling
Algorithms
ARTIFICIAL INTELLIGENCE
Intelligent agents
Evolutionary Scheduling
Weighted Tardiness
Crossover Operators
genetic diversity
description 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.
format Objeto de conferencia
Objeto de conferencia
author San Pedro, María Eugenia de
Pandolfi, Daniel
Villagra, Andrea
Lasso, Marta Graciela
Gallard, Raúl Hector
author_facet San Pedro, María Eugenia de
Pandolfi, Daniel
Villagra, Andrea
Lasso, Marta Graciela
Gallard, Raúl Hector
author_sort San Pedro, María Eugenia de
title Influence of crossover operators in evolutionary scheduling under multirecombined schemes
title_short Influence of crossover operators in evolutionary scheduling under multirecombined schemes
title_full Influence of crossover operators in evolutionary scheduling under multirecombined schemes
title_fullStr Influence of crossover operators in evolutionary scheduling under multirecombined schemes
title_full_unstemmed Influence of crossover operators in evolutionary scheduling under multirecombined schemes
title_sort influence of crossover operators in evolutionary scheduling under multirecombined schemes
publishDate 2003
url http://sedici.unlp.edu.ar/handle/10915/22729
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AT lassomartagraciela influenceofcrossoveroperatorsinevolutionaryschedulingundermultirecombinedschemes
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