Self adaptive cluster based and weed inspired differential evolution algorithm for real world optimization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F11%3A86097049" target="_blank" >RIV/61989100:27240/11:86097049 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/CEC.2011.5949694" target="_blank" >http://dx.doi.org/10.1109/CEC.2011.5949694</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CEC.2011.5949694" target="_blank" >10.1109/CEC.2011.5949694</a>
Alternative languages
Result language
angličtina
Original language name
Self adaptive cluster based and weed inspired differential evolution algorithm for real world optimization
Original language description
In this paper we propose a Self Adaptive Cluster based and Weed Inspired Differential Evolution algorithm (SACWIDE), the total population is divided into several clusters based on the positions of the individuals and the cluster number is dynamically changed by the suitable learning strategy during evolution. Here we incorporate a modified version of the Invasive Weed Optimization (IWO) algorithm as a local search technique. The algorithm strategically determines whether a particular cluster will perform Differential Evolution (DE) or the IWO algorithm (modified). The number of clusters in a particular iteration is set by the algorithm itself self-adaptively. The performance of SACWIDE is reported on the set of 22 benchmark problems of CEC-2011. (C) 2011 IEEE
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA102%2F09%2F1494" target="_blank" >GA102/09/1494: New methods od data transmition based on turbo code</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2011 IEEE Congress of Evolutionary Computation, CEC 2011
ISBN
978-1-4244-7834-7
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
750-756
Publisher name
IEEE
Place of publication
Vienna
Event location
New Orleans
Event date
Jun 5, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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