About: Exponential Crossover in Competive Differential Evolution     Goto   Sponge   NotDistinct   Permalink

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  • Two types of crossover in differential evolution algorithms are concerned, both in standard and adaptive variants of differential evolution. Proper choice of mutation probability in exponential crossover is proposed and implemented in respective variants of differential evolution in tests. The impact of crossover type and the use of random localization in mutation were examined in benchmark tests. New variant of self-adaptive differential evolution with both type of crossover and competitive setting of control parameters outperformed the others. This variant is suggested for the real-world problems, where we need an adaptive algorithm applicable without time-wasting parameter tuning.
  • Two types of crossover in differential evolution algorithms are concerned, both in standard and adaptive variants of differential evolution. Proper choice of mutation probability in exponential crossover is proposed and implemented in respective variants of differential evolution in tests. The impact of crossover type and the use of random localization in mutation were examined in benchmark tests. New variant of self-adaptive differential evolution with both type of crossover and competitive setting of control parameters outperformed the others. This variant is suggested for the real-world problems, where we need an adaptive algorithm applicable without time-wasting parameter tuning. (en)
Title
  • Exponential Crossover in Competive Differential Evolution
  • Exponential Crossover in Competive Differential Evolution (en)
skos:prefLabel
  • Exponential Crossover in Competive Differential Evolution
  • Exponential Crossover in Competive Differential Evolution (en)
skos:notation
  • RIV/61988987:17310/08:A1000PRX!RIV10-MSM-17310___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(GA201/08/0472), Z(MSM6198898701)
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
  • 367384
http://linked.open...ai/riv/idVysledku
  • RIV/61988987:17310/08:A1000PRX
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • global optimization; differential evolution; control parameters; competitive adaption; exponential crossover; numerical comparison (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [289704B0A286]
http://linked.open...v/mistoKonaniAkce
  • Brno
http://linked.open...i/riv/mistoVydani
  • Brno
http://linked.open...i/riv/nazevZdroje
  • MENDEL 2008, 14th International Conference on Soft Computing
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Tvrdík, Josef
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000265681300009
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • University of Technology
https://schema.org/isbn
  • 978-80-214-3675-6
http://localhost/t...ganizacniJednotka
  • 17310
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