Artificial Weed Colonies with Neighbourhood Crowding Scheme for Multimodal Optimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86084578" target="_blank" >RIV/61989100:27240/12:86084578 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-81-322-0487-9_74" target="_blank" >http://dx.doi.org/10.1007/978-81-322-0487-9_74</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-81-322-0487-9_74" target="_blank" >10.1007/978-81-322-0487-9_74</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Artificial Weed Colonies with Neighbourhood Crowding Scheme for Multimodal Optimization

Popis výsledku v původním jazyce

Multimodal optimization is used to find multiple global & local optima which is very useful in many real world optimization problems. But often evolutionary algorithms fail to locate multiple optima as required by the system. Also they fail to store those optima by themselves. So we have to use other selection scheme that can detect & store multiple optima along with evolutionary algorithms. Hence we use niching which is a very powerful tool in detecting & storing multiple optima. Niching methods were introduced to EAs to allow maintenance of a population of diverse individuals so that multiple optima within a single population can be located.Crowding which is a very primitive branch of niching is used here as the selection scheme with Invasive Weed Optimization (IWO) which is a ecologically inspired algorithms depicting behaviors of plants. For multimodal optimization the total search space is divided into several niches in which separately IWO is applied to find the optima in niches.

Název v anglickém jazyce

Artificial Weed Colonies with Neighbourhood Crowding Scheme for Multimodal Optimization

Popis výsledku anglicky

Multimodal optimization is used to find multiple global & local optima which is very useful in many real world optimization problems. But often evolutionary algorithms fail to locate multiple optima as required by the system. Also they fail to store those optima by themselves. So we have to use other selection scheme that can detect & store multiple optima along with evolutionary algorithms. Hence we use niching which is a very powerful tool in detecting & storing multiple optima. Niching methods were introduced to EAs to allow maintenance of a population of diverse individuals so that multiple optima within a single population can be located.Crowding which is a very primitive branch of niching is used here as the selection scheme with Invasive Weed Optimization (IWO) which is a ecologically inspired algorithms depicting behaviors of plants. For multimodal optimization the total search space is divided into several niches in which separately IWO is applied to find the optima in niches.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název statě ve sborníku

Advances in Intelligent and Soft Computing. Volume 130

ISBN

978-81-322-0486-2

ISSN

1867-5662

e-ISSN

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Počet stran výsledku

9

Strana od-do

779-787

Název nakladatele

Springer India

Místo vydání

Delhi

Místo konání akce

Roorkee

Datum konání akce

20. 12. 2011

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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