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Statements

Subject Item
n2:RIV%2F61989100%3A27740%2F13%3A86089240%21RIV14-MSM-27740___
rdf:type
skos:Concept n10:Vysledek
dcterms:description
Stochastic nature-inspired optimization and search methods depend on streams of integer and floating point 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) and environmental effects (small random changes in motion direction and velocity). Deterministic chaos is a well known mathematical concept that can be used to generate sequences of seemingly random real numbers within selected interval in a predictable and controllable way. 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, differential evolution, and particle swarm optimization using different pseudo-random number generators and chaotic systems as sources of stochasticity. Stochastic nature-inspired optimization and search methods depend on streams of integer and floating point 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) and environmental effects (small random changes in motion direction and velocity). Deterministic chaos is a well known mathematical concept that can be used to generate sequences of seemingly random real numbers within selected interval in a predictable and controllable way. 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, differential evolution, and particle swarm optimization using different pseudo-random number generators and chaotic systems as sources of stochasticity.
dcterms:title
On the use of chaos in nature-inspired optimization methods On the use of chaos in nature-inspired optimization methods
skos:prefLabel
On the use of chaos in nature-inspired optimization methods On the use of chaos in nature-inspired optimization methods
skos:notation
RIV/61989100:27740/13:86089240!RIV14-MSM-27740___
n10:predkladatel
n11:orjk%3A27740
n3:aktivita
n8:S n8:P
n3:aktivity
P(ED1.1.00/02.0070), P(EE.2.3.20.0073), S
n3:dodaniDat
n19:2014
n3:domaciTvurceVysledku
n16:9175970 n16:3433390 n16:4347269
n3:druhVysledku
n15:D
n3:duvernostUdaju
n4:S
n3:entitaPredkladatele
n17:predkladatel
n3:idSjednocenehoVysledku
93978
n3:idVysledku
RIV/61989100:27740/13:86089240
n3:jazykVysledku
n13:eng
n3:klicovaSlova
Simulation; Pseudo-random number generators; Particle swarm optimization; Genetic algorithms; Differential evolution; Deterministic chaos
n3:klicoveSlovo
n6:Genetic%20algorithms n6:Differential%20evolution n6:Deterministic%20chaos n6:Pseudo-random%20number%20generators n6:Particle%20swarm%20optimization n6:Simulation
n3:kontrolniKodProRIV
[8B6EF53C6317]
n3:mistoKonaniAkce
Manchester
n3:mistoVydani
New York
n3:nazevZdroje
Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
n3:obor
n22:IN
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:projekt
n20:ED1.1.00%2F02.0070 n20:EE.2.3.20.0073
n3:rokUplatneniVysledku
n19:2013
n3:tvurceVysledku
Krömer, Pavel Snášel, Václav Zelinka, Ivan
n3:typAkce
n7:WRD
n3:zahajeniAkce
2013-10-13+02:00
s:numberOfPages
6
n23:doi
10.1109/SMC.2013.290
n14:hasPublisher
IEEE
n9:isbn
978-0-7695-5154-8
n12:organizacniJednotka
27740