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Chaotic Attributes and Permutative Optimization

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dc.title Chaotic Attributes and Permutative Optimization en
dc.contributor.author Davendra, Donald David
dc.contributor.author Zelinka, Ivan
dc.contributor.author Onwubolu, Godfrey
dc.relation.ispartof Evolutionary Algorithms and Chaotic Systems
dc.identifier.isbn 978-3-642-10706-1
dc.date.issued 2010
dc.event.location Heidelberg
utb.event.state-en Germany
utb.event.state-cs Německo
dc.type bookPart
dc.language.iso en
dc.publisher Springer-Verlag. Berlin
dc.subject Chaos en
dc.subject Optimization en
dc.subject Evolutionary algorithms en
dc.subject SOMA en
dc.subject Differential Evolution en
dc.subject Genetic Algorithm en
dc.subject Combinatorial Optimitzation en
dc.description.abstract Population dynamics and its relation to chaotic systems is analyzed in this Chapter. Using basic chaotic principles of attractors and edges, a dynamic population is developed, which is used to induce and retain diversity in a metaheuristic population. Simulation is done with Genetic Algorithm, Differential Evolution and Self-Organizing Migrating Algorithm on the combinatorial problem of Quadratic Assignment with promising results. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1006046
utb.identifier.rivid RIV/70883521:28140/10:63508867!RIV11-GA0-28140___
utb.identifier.obdid 43864617
utb.source c-riv
dc.date.accessioned 2016-04-28T10:37:39Z
dc.date.available 2016-04-28T10:37:39Z
dc.description.sponsorship P(GA102/09/1680), Z(MSM7088352101)
dc.format.extent 521
utb.identifier.utb-sysno 63240
utb.identifier.nkp 5222916
utb.contributor.internalauthor Davendra, Donald David
utb.contributor.internalauthor Zelinka, Ivan
riv.obor IN
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