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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. (en)
Title
  • Optimizers Derived from Human Opinion Formation
  • Optimizers Derived from Human Opinion Formation (en)
skos:prefLabel
  • Optimizers Derived from Human Opinion Formation
  • Optimizers Derived from Human Opinion Formation (en)
skos:notation
  • RIV/68407700:21230/11:00186233!RIV12-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM6840770012)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 218791
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/11:00186233
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Swarm Intelligence; Opinion Formation Models; Binary Optimization (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [DCF169878BD3]
http://linked.open...v/mistoKonaniAkce
  • Salamanca
http://linked.open...i/riv/mistoVydani
  • New York
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 2011 Third World Congress on Nature and Biologically Inspired Computing
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Lhotská, Lenka
  • Macaš, Martin
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/NaBIC.2011.6089618
http://purl.org/ne...btex#hasPublisher
  • IEEE - Systems, Man, and Cybernetics Society
https://schema.org/isbn
  • 978-1-4577-1123-7
http://localhost/t...ganizacniJednotka
  • 21230
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