Genetic Algorithm using Theory of Chaos

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F15%3APU116947" target="_blank" >RIV/00216305:26230/15:PU116947 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.fit.vutbr.cz/research/pubs/all.php?id=10781" target="_blank" >http://www.fit.vutbr.cz/research/pubs/all.php?id=10781</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.procs.2015.05.248" target="_blank" >10.1016/j.procs.2015.05.248</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Genetic Algorithm using Theory of Chaos

Popis výsledku v původním jazyce

This paper is focused on genetic algorithm with chaotic crossover operator. We have performed some experiments to study possible use of chaos in simulated evolution. A novel genetic algorithm with chaotic optimization operation is proposed to optimization of multimodal functions. As the basis of a new crossing operator a simple equation involving chaos is used, concrete the logistic function. The logistic function is a simple one-parameter function of the second order that shows a chaotic behavior for some values of the parameter. Generally, solution of the logistic function has three areas of its behavior: convergent, periodic and chaotic. We have supposed that the convergent behavior leads to exploitation and the chaotic behavior aids to exploration. The periodic behavior is probably neutral and thus it is a negligible one. Results of our experiments conrm these expectations. A proposed genetic algorithm with chaotic crossover operator leads to a more ecient computation in comparison with the traditional genetic algorithm.

Název v anglickém jazyce

Genetic Algorithm using Theory of Chaos

Popis výsledku anglicky

This paper is focused on genetic algorithm with chaotic crossover operator. We have performed some experiments to study possible use of chaos in simulated evolution. A novel genetic algorithm with chaotic optimization operation is proposed to optimization of multimodal functions. As the basis of a new crossing operator a simple equation involving chaos is used, concrete the logistic function. The logistic function is a simple one-parameter function of the second order that shows a chaotic behavior for some values of the parameter. Generally, solution of the logistic function has three areas of its behavior: convergent, periodic and chaotic. We have supposed that the convergent behavior leads to exploitation and the chaotic behavior aids to exploration. The periodic behavior is probably neutral and thus it is a negligible one. Results of our experiments conrm these expectations. A proposed genetic algorithm with chaotic crossover operator leads to a more ecient computation in comparison with the traditional genetic algorithm.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Procedia Computer Science

ISSN

1877-0509

e-ISSN

—

Svazek periodika

2015

Číslo periodika v rámci svazku

51

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

10

Strana od-do

316-325

Kód UT WoS článku

000373939100032

EID výsledku v databázi Scopus

2-s2.0-84939209113