An evolutionary algorithm to track changes of optimum value locations in dynamic environments

Non-stationary, or dynamic, problems change over time. There exist a variety of forms of dynamism. The concept of dynamic environments in the context of this paper means that the fitness landscape changes during the run of an evolutionary algorithm. Genetic diversity is crucial to provide the neces...

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Detalles Bibliográficos
Autores principales: Aragón, Victoria S., Esquivel, Susana Cecilia
Formato: Articulo
Lenguaje:Inglés
Publicado: 2004
Materias:
Ciencias Informáticas
genetic diversity
macromutation operators
Algorithms
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/9493
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct04-1.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-9493
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
genetic diversity
macromutation operators
Algorithms
spellingShingle Ciencias Informáticas
genetic diversity
macromutation operators
Algorithms
Aragón, Victoria S.
Esquivel, Susana Cecilia
An evolutionary algorithm to track changes of optimum value locations in dynamic environments
topic_facet Ciencias Informáticas
genetic diversity
macromutation operators
Algorithms
description Non-stationary, or dynamic, problems change over time. There exist a variety of forms of dynamism. The concept of dynamic environments in the context of this paper means that the fitness landscape changes during the run of an evolutionary algorithm. Genetic diversity is crucial to provide the necessary adaptability of the algorithm to changes. Two mechanism of macromutation are incorporated to the algorithm to maintain genetic diversity in the population. The algorithm was tested on a set of dynamic testing functions provided by a dynamic fitness problem generator. The main goal was to determinate the algorithm´s ability to reacting to changes of optimum values that alter their locations, so that the optimum value can still be tracked when dimensional and multimodal scalability in the functions is adjusted. The effectiveness and limitations of the proposed algorithm is discussed from results empirically obtained.
format Articulo
Articulo
author Aragón, Victoria S.
Esquivel, Susana Cecilia
author_facet Aragón, Victoria S.
Esquivel, Susana Cecilia
author_sort Aragón, Victoria S.
title An evolutionary algorithm to track changes of optimum value locations in dynamic environments
title_short An evolutionary algorithm to track changes of optimum value locations in dynamic environments
title_full An evolutionary algorithm to track changes of optimum value locations in dynamic environments
title_fullStr An evolutionary algorithm to track changes of optimum value locations in dynamic environments
title_full_unstemmed An evolutionary algorithm to track changes of optimum value locations in dynamic environments
title_sort evolutionary algorithm to track changes of optimum value locations in dynamic environments
publishDate 2004
url http://sedici.unlp.edu.ar/handle/10915/9493
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct04-1.pdf
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