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Soft Computing

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01.06.2013 | Focus

A performance study on synchronicity and neighborhood size in particle swarm optimization

verfasst von: Juan Rada-Vilela, Mengjie Zhang, Winston Seah

Erschienen in: Soft Computing | Ausgabe 6/2013

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Abstract

This article presents a performance study on the effect of synchronicity in communications and neighborhood size in Particle Swarm Optimization (PSO) on large-scale optimization problems. The algorithms under study are the Synchronous PSO (S-PSO), the Asynchronous PSO (A-PSO), and the recently proposed Random Asynchronous PSO (RA-PSO), all of which are evaluated upon the set of benchmark functions presented at the IEEE CEC’2010 special session and competition on large-scale global optimization. Results show that RA-PSO has the best general performance in large neighborhoods, while S-PSO has the best one in small neighborhoods. Rigorous statistical analyses support our observations and provide a guideline on the performance of the algorithms under different neighborhood sizes.

Vorheriger Artikel Best practices in measuring algorithm performance for dynamic optimization problems

Nächster Artikel Computational results for an automatically tuned CMA-ES with increasing population size on the CEC’05 benchmark set

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Titel: A performance study on synchronicity and neighborhood size in particle swarm optimization
verfasst von: Juan Rada-Vilela
Mengjie Zhang
Winston Seah
Publikationsdatum: 01.06.2013
Verlag: Springer-Verlag
Erschienen in: Soft Computing / Ausgabe 6/2013
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-013-1015-9

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