An Effective Hybrid Firefly Algorithm with Harmony Search for Global Numerical Optimization

A hybrid metaheuristic approach by hybridizing harmony search (HS) and firefly algorithm (FA), namely, HS/FA, is proposed to solve function optimization. In HS/FA, the exploration of HS and the exploitation of FA are fully exerted, so HS/FA has a faster convergence speed than HS and FA. Also, top fi...

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Detalles Bibliográficos
Autores principales: Guo, Lihong, Wang, Gai-Ge, Wang, Heqi, Wang, Dinan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3856164/
https://www.ncbi.nlm.nih.gov/pubmed/24348137
http://dx.doi.org/10.1155/2013/125625
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author Guo, Lihong
Wang, Gai-Ge
Wang, Heqi
Wang, Dinan
author_facet Guo, Lihong
Wang, Gai-Ge
Wang, Heqi
Wang, Dinan
author_sort Guo, Lihong
collection PubMed
description A hybrid metaheuristic approach by hybridizing harmony search (HS) and firefly algorithm (FA), namely, HS/FA, is proposed to solve function optimization. In HS/FA, the exploration of HS and the exploitation of FA are fully exerted, so HS/FA has a faster convergence speed than HS and FA. Also, top fireflies scheme is introduced to reduce running time, and HS is utilized to mutate between fireflies when updating fireflies. The HS/FA method is verified by various benchmarks. From the experiments, the implementation of HS/FA is better than the standard FA and other eight optimization methods.
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spelling pubmed-38561642013-12-16 An Effective Hybrid Firefly Algorithm with Harmony Search for Global Numerical Optimization Guo, Lihong Wang, Gai-Ge Wang, Heqi Wang, Dinan ScientificWorldJournal Research Article A hybrid metaheuristic approach by hybridizing harmony search (HS) and firefly algorithm (FA), namely, HS/FA, is proposed to solve function optimization. In HS/FA, the exploration of HS and the exploitation of FA are fully exerted, so HS/FA has a faster convergence speed than HS and FA. Also, top fireflies scheme is introduced to reduce running time, and HS is utilized to mutate between fireflies when updating fireflies. The HS/FA method is verified by various benchmarks. From the experiments, the implementation of HS/FA is better than the standard FA and other eight optimization methods. Hindawi Publishing Corporation 2013-11-20 /pmc/articles/PMC3856164/ /pubmed/24348137 http://dx.doi.org/10.1155/2013/125625 Text en Copyright © 2013 Lihong Guo et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Guo, Lihong
Wang, Gai-Ge
Wang, Heqi
Wang, Dinan
An Effective Hybrid Firefly Algorithm with Harmony Search for Global Numerical Optimization
title An Effective Hybrid Firefly Algorithm with Harmony Search for Global Numerical Optimization
title_full An Effective Hybrid Firefly Algorithm with Harmony Search for Global Numerical Optimization
title_fullStr An Effective Hybrid Firefly Algorithm with Harmony Search for Global Numerical Optimization
title_full_unstemmed An Effective Hybrid Firefly Algorithm with Harmony Search for Global Numerical Optimization
title_short An Effective Hybrid Firefly Algorithm with Harmony Search for Global Numerical Optimization
title_sort effective hybrid firefly algorithm with harmony search for global numerical optimization
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3856164/
https://www.ncbi.nlm.nih.gov/pubmed/24348137
http://dx.doi.org/10.1155/2013/125625
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