DE with Random Vector based Mutatiton for High Dimensional Problems

Metaheuristic techniques are the current standard for solving optimization problems. Differential Evolution (DE) is one of the most used because all operations are on real floating point numbers and does not require extra coding. However, the performance shown by DE could decay when applied in probl...

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Autores principales: Hernández, Sebastián, Mezura Montes, Efrén, Leguizamón, Guillermo
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2019
Materias:
Ciencias Informáticas
Differential evolution
High-dimensional optimization problem
Local search
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/90893
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-90893
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
Differential evolution
High-dimensional optimization problem
Local search
spellingShingle Ciencias Informáticas
Differential evolution
High-dimensional optimization problem
Local search
Hernández, Sebastián
Mezura Montes, Efrén
Leguizamón, Guillermo
DE with Random Vector based Mutatiton for High Dimensional Problems
topic_facet Ciencias Informáticas
Differential evolution
High-dimensional optimization problem
Local search
description Metaheuristic techniques are the current standard for solving optimization problems. Differential Evolution (DE) is one of the most used because all operations are on real floating point numbers and does not require extra coding. However, the performance shown by DE could decay when applied in problems of high dimensionality. In this paper we present RLSDE, a modified version of DE, based on a random vector as a scaling factor for the differential mutation and the application of a local search operator. These modifications constitute an algorithm capable of solving 100D problems using few computational resources. RLSDE is compared against the results obtained with the classic version of DE and ELSDE (Enchanced Local Search Differential Evolution), showing the performance of the proposal.
format Objeto de conferencia
Objeto de conferencia
author Hernández, Sebastián
Mezura Montes, Efrén
Leguizamón, Guillermo
author_facet Hernández, Sebastián
Mezura Montes, Efrén
Leguizamón, Guillermo
author_sort Hernández, Sebastián
title DE with Random Vector based Mutatiton for High Dimensional Problems
title_short DE with Random Vector based Mutatiton for High Dimensional Problems
title_full DE with Random Vector based Mutatiton for High Dimensional Problems
title_fullStr DE with Random Vector based Mutatiton for High Dimensional Problems
title_full_unstemmed DE with Random Vector based Mutatiton for High Dimensional Problems
title_sort de with random vector based mutatiton for high dimensional problems
publishDate 2019
url http://sedici.unlp.edu.ar/handle/10915/90893
work_keys_str_mv AT hernandezsebastian dewithrandomvectorbasedmutatitonforhighdimensionalproblems
AT mezuramontesefren dewithrandomvectorbasedmutatitonforhighdimensionalproblems
AT leguizamonguillermo dewithrandomvectorbasedmutatitonforhighdimensionalproblems
bdutipo_str Repositorios
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