On Analysis and Performance Improvement of Evolutionary Algorithms Based on its Complex Network Structure A Summary Overview

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86096908" target="_blank" >RIV/61989100:27240/15:86096908 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007/978-3-319-27060-9_32" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-27060-9_32</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-27060-9_32" target="_blank" >10.1007/978-3-319-27060-9_32</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On Analysis and Performance Improvement of Evolutionary Algorithms Based on its Complex Network Structure A Summary Overview

Popis výsledku v původním jazyce

In this participation there is sketched and explained mutual intersection between complex networks and evolutionary computation including summarization of our previous results. It is sketched how dynamics of evolutionary algorithm can be converted into acomplex network and based on its properties like degree centrality etc. can be improved performance of used evolutionary algorithm. Results presented here are currently numerical demonstration rather than theoretical mathematical proofs. Paper discussesresults from differential evolution, self-organizing migrating algorithm, genetic algorithms and artificial bee colony. We open question whether evolutionary algorithms really create complex network structures and whether this knowledge can be successfully used like feedback for control of evolutionary dynamics and its improvement in order to increase the performance of evolutionary algorithms.

Název v anglickém jazyce

On Analysis and Performance Improvement of Evolutionary Algorithms Based on its Complex Network Structure A Summary Overview

Popis výsledku anglicky

In this participation there is sketched and explained mutual intersection between complex networks and evolutionary computation including summarization of our previous results. It is sketched how dynamics of evolutionary algorithm can be converted into acomplex network and based on its properties like degree centrality etc. can be improved performance of used evolutionary algorithm. Results presented here are currently numerical demonstration rather than theoretical mathematical proofs. Paper discussesresults from differential evolution, self-organizing migrating algorithm, genetic algorithms and artificial bee colony. We open question whether evolutionary algorithms really create complex network structures and whether this knowledge can be successfully used like feedback for control of evolutionary dynamics and its improvement in order to increase the performance of evolutionary algorithms.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA15-06700S" target="_blank" >GA15-06700S: Nekonvenční řízení komplexních systémů</a><br>

Návaznosti

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 statě ve sborníku

Lecture Notes in Computer Science. Volume 9413

ISBN

978-3-319-27059-3

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

12

Strana od-do

389-400

Název nakladatele

Springer Verlag

Místo vydání

London

Místo konání akce

Morelos

Datum konání akce

25. 10. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000367681700032