NDLI: FlockOpt: A new swarm optimization algorithm based on collective behavior of starling birds

Content Provider	IEEE Xplore Digital Library
Author	Hereford, J. Blum, C.
Copyright Year	2011
Description	Author affiliation: Department of Engineering and Physics, Murray State University, KY 42071 USA (Hereford, J.) \|\| ALBCOM Research Group, Universitat Politècnica de Catalunya, Barcelona, Spain (Blum, C.)
Abstract	The aim of this paper is to introduce a new algorithm, FlockOpt, for real-parameter optimization. The proposed algorithm is inspired by a recent model of the flocking behaviour of starling birds and combines the main elements of this model with additional features from Swarm Intelligence. The results of from FlockOpt are compared to the results of generic versions of Particle Swarm Optimization, which is the closest relative of FlockOpt from the Swarm Intelligence field. The comparison shows that FlockOpt is able to beat the generic versions of particle swarm optimization in the majority of the test cases. Interesting features such as the attraction, repulsion and the alignment between members of the population make FlockOpt quite attractive for further examination.
Starting Page	17
Ending Page	22
File Size	703769
Page Count	6
File Format	PDF
ISBN	9781457711220
e-ISBN	9781457711244
DOI	10.1109/NaBIC.2011.6089411
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-19
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	FlockOpt Flowcharts Current measurement Particle Swarm Optimization (PSO) Starling bird model Birds Swarm intelligence Mathematical model Particle swarm optimization Equations Optimization
Content Type	Text
Resource Type	Article

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