A taxonomy of heterogeneity and dynamics in particle swarm optimisation

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We propose a taxonomy for heterogeneity and dynamics of swarms in PSO, which separates the consideration of homogeneity and heterogeneity from the presence of adaptive and non-adaptive dynamics, both at the particle and swarm level. It thus supports research into the separate and combined contributions of each of these characteristics. An analysis of the literature shows that most recent work has focussed on only parts of the taxonomy. Our results agree with prior work that both heterogeneity and dynamics are useful. However while heterogeneity does typically improve PSO, this is often dominated by the improvement due to dynamics. Adaptive strategies used to generate heterogeneity may end up sacrificing the dynamics which provide the greatest performance increase. We evaluate exemplar strategies for each area of the taxonomy and conclude with recommendations.

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Publication date31 Dec 2014
Publication titleParallel Problem Solving from Nature - PPSN XIII : 13th international conference, Ljubljana, Slovenia, September 13-17, 2014. Proceedings
EditorsThomas Bartz-Beielstein, Jürgen Branke, Bogdan Filipič, Jim Smith
Number of pages10
ISBN (Electronic)978-3-319-10762-2
ISBN (Print)978-3-319-10761-5
Original languageEnglish
Event13th international conference on Parallel Problem Solving from Nature - Ljubljana, Slovenia
Duration: 13 Sep 201417 Sep 2014

Publication series

NameLecture notes in computer science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference13th international conference on Parallel Problem Solving from Nature
Abbreviated titlePPSN XIII

Employable Graduates; Exploitable Research

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