The ant colony metaphor in continuous spaces using boundary search

This paper presents an application of the ant colony metaphor for continuous space optimization problems. The ant algortihm proposed works following the principle of the ant colony approach, i.e., a population of agents iteratively, cooperatively, and independently search for a solution. Each ant i...

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Detalles Bibliográficos
Autor principal: Leguizamón, Guillermo
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2003
Materias:
Ciencias Informáticas
Hormigas
Optimization
Algorithms
ARTIFICIAL INTELLIGENCE
Intelligent agents
ant colony optimization
evolutionary algorithms
constraint optimization problems
boundary search
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/22787
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-22787
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
Hormigas
Optimization
Algorithms
ARTIFICIAL INTELLIGENCE
Intelligent agents
ant colony optimization
evolutionary algorithms
constraint optimization problems
boundary search
spellingShingle Ciencias Informáticas
Hormigas
Optimization
Algorithms
ARTIFICIAL INTELLIGENCE
Intelligent agents
ant colony optimization
evolutionary algorithms
constraint optimization problems
boundary search
Leguizamón, Guillermo
The ant colony metaphor in continuous spaces using boundary search
topic_facet Ciencias Informáticas
Hormigas
Optimization
Algorithms
ARTIFICIAL INTELLIGENCE
Intelligent agents
ant colony optimization
evolutionary algorithms
constraint optimization problems
boundary search
description This paper presents an application of the ant colony metaphor for continuous space optimization problems. The ant algortihm proposed works following the principle of the ant colony approach, i.e., a population of agents iteratively, cooperatively, and independently search for a solution. Each ant in the distributed algorithm applies a local search operator which explores the neighborhood region of a particular point in the search space (individual search level). The local search operator is designed for exploring the boundary between the feasible and infeasible search space. On the other hand, each ant obtains global information from the colony in order to exploit the more promising regions of the search space (cooperation level). The ant colony based algorithm presented here was successfully applied to two widely studied and interesting constrained numerical optimization test cases.
format Objeto de conferencia
Objeto de conferencia
author Leguizamón, Guillermo
author_facet Leguizamón, Guillermo
author_sort Leguizamón, Guillermo
title The ant colony metaphor in continuous spaces using boundary search
title_short The ant colony metaphor in continuous spaces using boundary search
title_full The ant colony metaphor in continuous spaces using boundary search
title_fullStr The ant colony metaphor in continuous spaces using boundary search
title_full_unstemmed The ant colony metaphor in continuous spaces using boundary search
title_sort ant colony metaphor in continuous spaces using boundary search
publishDate 2003
url http://sedici.unlp.edu.ar/handle/10915/22787
work_keys_str_mv AT leguizamonguillermo theantcolonymetaphorincontinuousspacesusingboundarysearch
AT leguizamonguillermo antcolonymetaphorincontinuousspacesusingboundarysearch
bdutipo_str Repositorios
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