An approach to support generic topologies in distributed PSO algorithms in Spark

Particle Swarm Optimization (PSO) is a popular population-based search algorithm that has been applied to all kinds of complex optimization problems. Although the performance of the algorithm strongly depends on the social topology that determines the interaction between the particles during the sea...

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Autores principales: Pardo, Xoán C., González, Patricia, Banga, Julio R., Doallo, Ramón
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2023
Materias:
Ciencias Informáticas
Particle Swarm Optimization
Metaheuristic Optimization Frameworks
Social topology
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/155416
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-155416
record_format dspace
spelling I19-R120-10915-1554162023-07-11T20:01:44Z http://sedici.unlp.edu.ar/handle/10915/155416 isbn:978-950-34-2271-7 An approach to support generic topologies in distributed PSO algorithms in Spark Pardo, Xoán C. González, Patricia Banga, Julio R. Doallo, Ramón 2023-06 2023 2023-07-11T16:56:12Z en Ciencias Informáticas Particle Swarm Optimization Metaheuristic Optimization Frameworks Social topology Particle Swarm Optimization (PSO) is a popular population-based search algorithm that has been applied to all kinds of complex optimization problems. Although the performance of the algorithm strongly depends on the social topology that determines the interaction between the particles during the search, current Metaheuristic Optimization Frameworks (MOFs) provide limited support for topologies. In this paper, we present an approach to support generic topologies in distributed PSO algorithms within a framework for the development and execution of populationbased metaheuristics in Spark, which is currently under development. Facultad de Informática Objeto de conferencia Objeto de conferencia http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf 2-7
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Particle Swarm Optimization
Metaheuristic Optimization Frameworks
Social topology
spellingShingle Ciencias Informáticas
Particle Swarm Optimization
Metaheuristic Optimization Frameworks
Social topology
Pardo, Xoán C.
González, Patricia
Banga, Julio R.
Doallo, Ramón
An approach to support generic topologies in distributed PSO algorithms in Spark
topic_facet Ciencias Informáticas
Particle Swarm Optimization
Metaheuristic Optimization Frameworks
Social topology
description Particle Swarm Optimization (PSO) is a popular population-based search algorithm that has been applied to all kinds of complex optimization problems. Although the performance of the algorithm strongly depends on the social topology that determines the interaction between the particles during the search, current Metaheuristic Optimization Frameworks (MOFs) provide limited support for topologies. In this paper, we present an approach to support generic topologies in distributed PSO algorithms within a framework for the development and execution of populationbased metaheuristics in Spark, which is currently under development.
format Objeto de conferencia
Objeto de conferencia
author Pardo, Xoán C.
González, Patricia
Banga, Julio R.
Doallo, Ramón
author_facet Pardo, Xoán C.
González, Patricia
Banga, Julio R.
Doallo, Ramón
author_sort Pardo, Xoán C.
title An approach to support generic topologies in distributed PSO algorithms in Spark
title_short An approach to support generic topologies in distributed PSO algorithms in Spark
title_full An approach to support generic topologies in distributed PSO algorithms in Spark
title_fullStr An approach to support generic topologies in distributed PSO algorithms in Spark
title_full_unstemmed An approach to support generic topologies in distributed PSO algorithms in Spark
title_sort approach to support generic topologies in distributed pso algorithms in spark
publishDate 2023
url http://sedici.unlp.edu.ar/handle/10915/155416
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AT doalloramon anapproachtosupportgenerictopologiesindistributedpsoalgorithmsinspark
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AT gonzalezpatricia approachtosupportgenerictopologiesindistributedpsoalgorithmsinspark
AT bangajulior approachtosupportgenerictopologiesindistributedpsoalgorithmsinspark
AT doalloramon approachtosupportgenerictopologiesindistributedpsoalgorithmsinspark
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