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

Result code in 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>

Alternative codes found

RIV/61989100:27740/14:86092554

Result on the web

<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>

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

IN - Informatics

OECD FORD branch

—

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2014

Confidentiality

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

Article name in the collection

Advances in Intelligent Systems and Computing. Volume 303

ISBN

978-3-319-08155-7

ISSN

2194-5357

e-ISSN

—

Number of pages

10

Pages from-to

151-160

Publisher name

Springer-Verlag Berlin Heidelberg

Place of publication

Berlin Heidelberg

Event location

Ostrava

Event date

Jun 23, 2014

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000342841800016