Hybrid differential artificial bee colony algorithm

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86092954" target="_blank" >RIV/61989100:27240/12:86092954 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1166/jctn.2012.2019" target="_blank" >http://dx.doi.org/10.1166/jctn.2012.2019</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1166/jctn.2012.2019" target="_blank" >10.1166/jctn.2012.2019</a>

Result language

angličtina

Original language name

Hybrid differential artificial bee colony algorithm

Original language description

Artificial Bee Colony Algorithm (ABCA) is a new population-based meta-heuristic approach inspired by the foraging behaviour of bees. This article describes an application of a novel Hybrid Differential Artificial Bee Colony Algorithm (HDABCA), which combines Differential Evolution strategy with Artificial Bee Colony algorithm. We illustrate the proposed method using several test functions and also compared with classical differential evolution algorithm and artificial bee colony algorithm. Simulation results illustrate that the proposed method is very efficient. Copyright 2012 American Scientific Publishers.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

IN - Informatics

OECD FORD branch

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Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2012

Confidentiality

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

Name of the periodical

Journal of Computational and Theoretical Nanoscience

ISSN

1546-1955

e-ISSN

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Volume of the periodical

9

Issue of the periodical within the volume

2

Country of publishing house

US - UNITED STATES

Number of pages

9

Pages from-to

249-257

UT code for WoS article

000302837800010

EID of the result in the Scopus database

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