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  • Evolutionary methods and stochastic algorithms in general rely heavily on streams of (pseudo-)random numbers generated in course of their execution. The pseudo-random numbers are utilized for in-silico emulation of probability-driven natural processes such as modification of genetic information (mutation, crossover), partner selection, and survival of the fittest (selection, migration). Deterministic chaos is a very well known mathematical concept that can be used to generate sequences of real numbers within selected interval. In the past, it has been used as a basis for various pseudo-random number generators with interesting properties. This work provides an empirical comparison of the performance of genetic algorithms and differential evolution using different pseudo-random number generators and chaotic systems as sources of stochasticity.
  • Evolutionary methods and stochastic algorithms in general rely heavily on streams of (pseudo-)random numbers generated in course of their execution. The pseudo-random numbers are utilized for in-silico emulation of probability-driven natural processes such as modification of genetic information (mutation, crossover), partner selection, and survival of the fittest (selection, migration). Deterministic chaos is a very well known mathematical concept that can be used to generate sequences of real numbers within selected interval. In the past, it has been used as a basis for various pseudo-random number generators with interesting properties. This work provides an empirical comparison of the performance of genetic algorithms and differential evolution using different pseudo-random number generators and chaotic systems as sources of stochasticity. (en)
Title
  • Randomness and chaos in genetic algorithms and differential evolution
  • Randomness and chaos in genetic algorithms and differential evolution (en)
skos:prefLabel
  • Randomness and chaos in genetic algorithms and differential evolution
  • Randomness and chaos in genetic algorithms and differential evolution (en)
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  • RIV/61989100:27740/13:86089186!RIV14-MSM-27740___
http://linked.open...avai/riv/aktivita
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  • P(ED1.1.00/02.0070), P(EE.2.3.20.0073), S
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  • 101443
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  • RIV/61989100:27740/13:86089186
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  • Simulation; Pseudo-random number generators; Genetic algorithms; Differential evolution; Deterministic chaos (en)
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  • [4CD16B17403A]
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  • Xi'an
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  • New York
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  • Proceedings - 5th International Conference on Intelligent Networking and Collaborative Systems, INCoS 2013
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  • Krömer, Pavel
  • Snášel, Václav
  • Zelinka, Ivan
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number of pages
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  • 10.1109/INCoS.2013.36
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  • IEEE
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  • 978-0-7695-4988-0
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  • 27740
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