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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F11%3A00186233%21RIV12-MSM-21230___
rdf:type
skos:Concept n6:Vysledek
rdfs:seeAlso
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6089618&tag=1
dcterms:description
The human opinion formation can be understood as a social approach to optimization. In the real world, the opinions encode a candidate solution, which is evaluated by a complex and unknown fitness function. The computer models of such processes can be slightly modified by introducing a fitness value, which leads to novel family of optimization techniques. This paper demonstrates how the novel algorithms can be derived from opinion formation models and empirically proves their usability in the area of binary optimization. Particularly, it introduces a general SITO algorithmic framework and describes three algorithms based on this general framework - the previously proposed original distance-based (oSITO), the simplified (sSITO) and the Galam inspired (gSITO) algorithm. The human opinion formation can be understood as a social approach to optimization. In the real world, the opinions encode a candidate solution, which is evaluated by a complex and unknown fitness function. The computer models of such processes can be slightly modified by introducing a fitness value, which leads to novel family of optimization techniques. This paper demonstrates how the novel algorithms can be derived from opinion formation models and empirically proves their usability in the area of binary optimization. Particularly, it introduces a general SITO algorithmic framework and describes three algorithms based on this general framework - the previously proposed original distance-based (oSITO), the simplified (sSITO) and the Galam inspired (gSITO) algorithm.
dcterms:title
Optimizers Derived from Human Opinion Formation Optimizers Derived from Human Opinion Formation
skos:prefLabel
Optimizers Derived from Human Opinion Formation Optimizers Derived from Human Opinion Formation
skos:notation
RIV/68407700:21230/11:00186233!RIV12-MSM-21230___
n6:predkladatel
n7:orjk%3A21230
n4:aktivita
n5:Z
n4:aktivity
Z(MSM6840770012)
n4:dodaniDat
n17:2012
n4:domaciTvurceVysledku
n22:6579191 n22:9431446
n4:druhVysledku
n11:D
n4:duvernostUdaju
n24:S
n4:entitaPredkladatele
n23:predkladatel
n4:idSjednocenehoVysledku
218791
n4:idVysledku
RIV/68407700:21230/11:00186233
n4:jazykVysledku
n14:eng
n4:klicovaSlova
Swarm Intelligence; Opinion Formation Models; Binary Optimization
n4:klicoveSlovo
n8:Swarm%20Intelligence n8:Opinion%20Formation%20Models n8:Binary%20Optimization
n4:kontrolniKodProRIV
[DCF169878BD3]
n4:mistoKonaniAkce
Salamanca
n4:mistoVydani
New York
n4:nazevZdroje
Proceedings of the 2011 Third World Congress on Nature and Biologically Inspired Computing
n4:obor
n10:JC
n4:pocetDomacichTvurcuVysledku
2
n4:pocetTvurcuVysledku
2
n4:rokUplatneniVysledku
n17:2011
n4:tvurceVysledku
Macaš, Martin Lhotská, Lenka
n4:typAkce
n12:WRD
n4:zahajeniAkce
2011-10-19+02:00
n4:zamer
n16:MSM6840770012
s:numberOfPages
6
n20:doi
10.1109/NaBIC.2011.6089618
n13:hasPublisher
IEEE - Systems, Man, and Cybernetics Society
n18:isbn
978-1-4577-1123-7
n9:organizacniJednotka
21230