A New Hybrid Particle Swarm Optimization with Variable Neighborhood Search for Solving Unconstrained Global Optimization Problems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092554" target="_blank" >RIV/61989100:27240/14:86092554 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/14:86092554

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-08156-4_16" target="_blank" >http://dx.doi.org/10.1007/978-3-319-08156-4_16</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-08156-4_16" target="_blank" >10.1007/978-3-319-08156-4_16</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A New Hybrid Particle Swarm Optimization with Variable Neighborhood Search for Solving Unconstrained Global Optimization Problems

Popis výsledku v původním jazyce

Over the past few decades, metaheuristics have been emerged to combine basic heuristic techniques in higher level frameworks to explore a search space in an efficient and an effective way. Particle swarm optimization (PSO) is one of the most important method in meta- heuristics methods, which is used for solving unconstrained global optimization prblems. In this paper, a new hybrid PSO algorithm is combined with variable neighborhood search (VNS) algorithm in order to search for the global optimal solutions for unconstrained global optimization problems. The proposed algorithm is called a hybrid particle swarm optimization with a variable neighborhood search algorithm (HPSOVNS). HPSOVNS aims to combine the PSO algorithm with its capability of making wide exploration and deep exploitation and the VNS algorithm as a local search algorithm to refine the overall best solution found so far in each iteration. In order to evaluate the performance of HPSOVNS, we compare its performance on nine different kinds of test benchmark functions with four particle swarm optimization based algorithms with different varieties. The results show that HPSOVNS algorithm achieves better performance and faster than the other algorithms. Springer International Publishing Switzerland 2014.

Název v anglickém jazyce

A New Hybrid Particle Swarm Optimization with Variable Neighborhood Search for Solving Unconstrained Global Optimization Problems

Popis výsledku anglicky

Over the past few decades, metaheuristics have been emerged to combine basic heuristic techniques in higher level frameworks to explore a search space in an efficient and an effective way. Particle swarm optimization (PSO) is one of the most important method in meta- heuristics methods, which is used for solving unconstrained global optimization prblems. In this paper, a new hybrid PSO algorithm is combined with variable neighborhood search (VNS) algorithm in order to search for the global optimal solutions for unconstrained global optimization problems. The proposed algorithm is called a hybrid particle swarm optimization with a variable neighborhood search algorithm (HPSOVNS). HPSOVNS aims to combine the PSO algorithm with its capability of making wide exploration and deep exploitation and the VNS algorithm as a local search algorithm to refine the overall best solution found so far in each iteration. In order to evaluate the performance of HPSOVNS, we compare its performance on nine different kinds of test benchmark functions with four particle swarm optimization based algorithms with different varieties. The results show that HPSOVNS algorithm achieves better performance and faster than the other algorithms. Springer International Publishing Switzerland 2014.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

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

Advances in Intelligent Systems and Computing. Volume 303

ISBN

978-3-319-08155-7

ISSN

2194-5357

e-ISSN

—

Počet stran výsledku

10

Strana od-do

151-160

Název nakladatele

Springer-Verlag Berlin Heidelberg

Místo vydání

Berlin Heidelberg

Místo konání akce

Ostrava

Datum konání akce

23. 6. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000342841800016