Self-adaptive differential particle swarm using a ring topology for multimodal optimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092819" target="_blank" >RIV/61989100:27240/14:86092819 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/14:86092819

Výsledek na webu

<a href="http://dx.doi.org/10.1109/ISDA.2013.6920430" target="_blank" >http://dx.doi.org/10.1109/ISDA.2013.6920430</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ISDA.2013.6920430" target="_blank" >10.1109/ISDA.2013.6920430</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Self-adaptive differential particle swarm using a ring topology for multimodal optimization

Popis výsledku v původním jazyce

During the last couple of decades, evolutionary and swarm intelligence algorithms have significantly advanced the state of the art for both discrete and numerical optimization. Without niching strategies, they usually converge to a single optimum, even in multimodal search spaces where numerous global or local solutions exist. In the literature, several niching approaches have been proposed for simultaneously computing multiple optima, though most of them require some user-specified parameters that should be calculated a priori, i.e. additional knowledge about the problem domain is required. Recently, it was demonstrated that particle swarm optimization (PSO) using a ring topology for neighborhood definition can give rise to robust and parameterless niching methods. Nevertheless, their performance dramatically worsens when the dimensionality of the solution space hikes, thus increasing the number of local optima. This paper aims at enhancing the performance of these types of PSO-based

Název v anglickém jazyce

Self-adaptive differential particle swarm using a ring topology for multimodal optimization

Popis výsledku anglicky

During the last couple of decades, evolutionary and swarm intelligence algorithms have significantly advanced the state of the art for both discrete and numerical optimization. Without niching strategies, they usually converge to a single optimum, even in multimodal search spaces where numerous global or local solutions exist. In the literature, several niching approaches have been proposed for simultaneously computing multiple optima, though most of them require some user-specified parameters that should be calculated a priori, i.e. additional knowledge about the problem domain is required. Recently, it was demonstrated that particle swarm optimization (PSO) using a ring topology for neighborhood definition can give rise to robust and parameterless niching methods. Nevertheless, their performance dramatically worsens when the dimensionality of the solution space hikes, thus increasing the number of local optima. This paper aims at enhancing the performance of these types of PSO-based

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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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)

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 2013 International Conference on Intelligent Systems Design and Applications (ISDA 2013) : Universiti Putra Malaysia, Malaysia, 08-10 December, 2013

ISBN

978-1-4799-3516-1

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

35-40

Název nakladatele

IEEE

Místo vydání

New York

Místo konání akce

Serdang, Selangor

Datum konání akce

8. 12. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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