NDLI: An exploration of topologies and communication in large particle swarms

Content Provider	IEEE Xplore Digital Library
Author	McNabb, A. Gardner, M. Seppi, K.
Copyright Year	2009
Description	Author affiliation: Department of Computer Science, Brigham Young University, 3361 TMCB, Provo, UT, USA (McNabb, A.; Gardner, M.; Seppi, K.)
Abstract	Particle Swarm Optimization (PSO) has typically been used with small swarms of about 50 particles. However, PSO is more efficiently parallelized with large swarms. We formally describe existing topologies and identify variations which are better suited to large swarms in both sequential and parallel computing environments. We examine the performance of PSO for benchmark functions with respect to swarm size and topology. We develop and demonstrate a new PSO variant which leverages the unique strengths of large swarms. “Hearsay PSO” allows for information to flow quickly through the swarm, even with very loosely connected topologies. These loosely connected topologies are well suited to large scale parallel computing environments because they require very little communication between particles. We consider the case where function evaluations are expensive with respect to communication as well as the case where function evaluations are relatively inexpensive. We also consider a situation where local communication is inexpensive compared to external communication, such as multicore systems in a cluster.
Starting Page	712
Ending Page	719
File Size	310299
Page Count	8
File Format	PDF
ISBN	9781424429585
DOI	10.1109/CEC.2009.4983015
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-18
Publisher Place	Norway
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Topology Particle swarm optimization Parallel processing Multicore processing Large-scale systems Clustering algorithms Convergence Birds Evolutionary computation Bioinformatics
Content Type	Text
Resource Type	Article

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