Publication detail

# Genetic Algorithm using Theory of Chaos

SNÁŠELOVÁ, P. ZBOŘIL, F.

Original Title

Genetic Algorithm using Theory of Chaos

English Title

Genetic Algorithm using Theory of Chaos

Type

journal article in Web of Science

Language

en

Original Abstract

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 conrm these expectations. A proposed genetic algorithm with chaotic crossover operator leads to a more ecient computation in comparison with the traditional genetic algorithm.

English abstract

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 conrm these expectations. A proposed genetic algorithm with chaotic crossover operator leads to a more ecient computation in comparison with the traditional genetic algorithm.

Keywords

optimization, genetic algorithm, chaos

RIV year

2015

Released

01.06.2015

Publisher

NEUVEDEN

Location

NEUVEDEN

Pages from

316

Pages to

325

Pages count

10

URL

BibTex

``````
@article{BUT119804,
author="Petra {Snášelová} and František {Zbořil}",
title="Genetic Algorithm using Theory of Chaos",
annote="
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
conrm these expectations. A proposed genetic algorithm with chaotic crossover
operator leads to a more ecient computation in comparison with the traditional
genetic algorithm.",