Hybrid Harmony Search algorithm for Global Optimization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F13%3A86089363" target="_blank" >RIV/61989100:27740/13:86089363 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/NaBIC.2013.6617841" target="_blank" >http://dx.doi.org/10.1109/NaBIC.2013.6617841</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/NaBIC.2013.6617841" target="_blank" >10.1109/NaBIC.2013.6617841</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Hybrid Harmony Search algorithm for Global Optimization

Popis výsledku v původním jazyce

This paper proposes two hybrid optimization methods based on Harmony Search algorithm (HS) and two different nature-inspired metaheuristic algorithms. In the first contribution, the combination was between the Improved Harmony Search (IHS) and the Particle Swarm Optimization (PSO). The second contribution merged the IHS with the Differential Evolution (DE) operators. The basic idea of hybridization was to ameliorate all the harmony memory vectors by adapting the PSO velocity or the DE operators in orderto increase the convergence speed. The new algorithms (IHSPSO and IHSDE) have been compared to the IHS, DE, PSO and some other algorithms like DHS and HSDM. The DHS and HSDM are two existing algorithms, which use different hybridization concepts betweenHS and DE. All of these algorithms have been evaluated by different test Benchmark functions. The results demonstrated that the hybrid algorithm IHSDE have the better convergence speed into the global optimum than the IHSPSO and the stan

Název v anglickém jazyce

Hybrid Harmony Search algorithm for Global Optimization

Popis výsledku anglicky

This paper proposes two hybrid optimization methods based on Harmony Search algorithm (HS) and two different nature-inspired metaheuristic algorithms. In the first contribution, the combination was between the Improved Harmony Search (IHS) and the Particle Swarm Optimization (PSO). The second contribution merged the IHS with the Differential Evolution (DE) operators. The basic idea of hybridization was to ameliorate all the harmony memory vectors by adapting the PSO velocity or the DE operators in orderto increase the convergence speed. The new algorithms (IHSPSO and IHSDE) have been compared to the IHS, DE, PSO and some other algorithms like DHS and HSDM. The DHS and HSDM are two existing algorithms, which use different hybridization concepts betweenHS and DE. All of these algorithms have been evaluated by different test Benchmark functions. The results demonstrated that the hybrid algorithm IHSDE have the better convergence speed into the global optimum than the IHSPSO and the stan

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

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

2013 World Congress on Nature and Biologically Inspired Computing, NaBIC 2013

ISBN

978-1-4799-1415-9

ISSN

—

e-ISSN

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Počet stran výsledku

7

Strana od-do

69-75

Název nakladatele

Elsevier

Místo vydání

New York

Místo konání akce

Fargo

Datum konání akce

12. 8. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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