A self-adaptive recombination method in evolutionary algorithms for solving epistatic problems

There are many different forms of recombination operators available in literature. However, it is difficult to determine a priori which one is the best suited for a given problem. This issue encourages us to propose an adaptive evolutionary algorithm to solve the NK landscape problem, which dynamica...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Stark, Natalia, Salto, Carolina
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2011
Materias:	Ciencias Informáticas Algorithms recombination operator; evolutionary algorithm; epistatic problems
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/18571
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-18571
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 Algorithms recombination operator; evolutionary algorithm; epistatic problems
spellingShingle	Ciencias Informáticas Algorithms recombination operator; evolutionary algorithm; epistatic problems Stark, Natalia Salto, Carolina A self-adaptive recombination method in evolutionary algorithms for solving epistatic problems
topic_facet	Ciencias Informáticas Algorithms recombination operator; evolutionary algorithm; epistatic problems
description	There are many different forms of recombination operators available in literature. However, it is difficult to determine a priori which one is the best suited for a given problem. This issue encourages us to propose an adaptive evolutionary algorithm to solve the NK landscape problem, which dynamically selects the recombination operator from an operator pool during the evolution; this removes the need of specifying a single recombinator operator ad-hoc. We compare the performance of our adaptive proposal against traditional evolutionary algorithms in a numerical way. Our experiments show that the simple adaptive mechanism has a good performance among all the evaluated ones on high dimensional landscapes with an additional reduction in pretuning time.
format	Objeto de conferencia Objeto de conferencia
author	Stark, Natalia Salto, Carolina
author_facet	Stark, Natalia Salto, Carolina
author_sort	Stark, Natalia
title	A self-adaptive recombination method in evolutionary algorithms for solving epistatic problems
title_short	A self-adaptive recombination method in evolutionary algorithms for solving epistatic problems
title_full	A self-adaptive recombination method in evolutionary algorithms for solving epistatic problems
title_fullStr	A self-adaptive recombination method in evolutionary algorithms for solving epistatic problems
title_full_unstemmed	A self-adaptive recombination method in evolutionary algorithms for solving epistatic problems
title_sort	self-adaptive recombination method in evolutionary algorithms for solving epistatic problems
publishDate	2011
url	http://sedici.unlp.edu.ar/handle/10915/18571
work_keys_str_mv	AT starknatalia aselfadaptiverecombinationmethodinevolutionaryalgorithmsforsolvingepistaticproblems AT saltocarolina aselfadaptiverecombinationmethodinevolutionaryalgorithmsforsolvingepistaticproblems AT starknatalia selfadaptiverecombinationmethodinevolutionaryalgorithmsforsolvingepistaticproblems AT saltocarolina selfadaptiverecombinationmethodinevolutionaryalgorithmsforsolvingepistaticproblems
bdutipo_str	Repositorios
_version_	1764820463066808322

A self-adaptive recombination method in evolutionary algorithms for solving epistatic problems

Ejemplares similares