A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization

A novel robust hybrid metaheuristic optimization approach, which can be considered as an improvement of the recently developed bat algorithm, is proposed to solve global numerical optimization problems. The improvement includes the addition of pitch adjustment operation in HS serving as a mutation o...

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Main Authors: Gaige Wang, Lihong Guo
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2013/696491
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author Gaige Wang
Lihong Guo
author_facet Gaige Wang
Lihong Guo
author_sort Gaige Wang
collection DOAJ
description A novel robust hybrid metaheuristic optimization approach, which can be considered as an improvement of the recently developed bat algorithm, is proposed to solve global numerical optimization problems. The improvement includes the addition of pitch adjustment operation in HS serving as a mutation operator during the process of the bat updating with the aim of speeding up convergence, thus making the approach more feasible for a wider range of real-world applications. The detailed implementation procedure for this improved metaheuristic method is also described. Fourteen standard benchmark functions are applied to verify the effects of these improvements, and it is demonstrated that, in most situations, the performance of this hybrid metaheuristic method (HS/BA) is superior to, or at least highly competitive with, the standard BA and other population-based optimization methods, such as ACO, BA, BBO, DE, ES, GA, HS, PSO, and SGA. The effect of the HS/BA parameters is also analyzed.
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institution Kabale University
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publishDate 2013-01-01
publisher Wiley
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series Journal of Applied Mathematics
spelling doaj-art-d280550b338a4bd6b188ad3983c11b682025-02-03T05:46:34ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/696491696491A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical OptimizationGaige Wang0Lihong Guo1Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaA novel robust hybrid metaheuristic optimization approach, which can be considered as an improvement of the recently developed bat algorithm, is proposed to solve global numerical optimization problems. The improvement includes the addition of pitch adjustment operation in HS serving as a mutation operator during the process of the bat updating with the aim of speeding up convergence, thus making the approach more feasible for a wider range of real-world applications. The detailed implementation procedure for this improved metaheuristic method is also described. Fourteen standard benchmark functions are applied to verify the effects of these improvements, and it is demonstrated that, in most situations, the performance of this hybrid metaheuristic method (HS/BA) is superior to, or at least highly competitive with, the standard BA and other population-based optimization methods, such as ACO, BA, BBO, DE, ES, GA, HS, PSO, and SGA. The effect of the HS/BA parameters is also analyzed.http://dx.doi.org/10.1155/2013/696491
spellingShingle Gaige Wang
Lihong Guo
A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization
Journal of Applied Mathematics
title A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization
title_full A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization
title_fullStr A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization
title_full_unstemmed A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization
title_short A Novel Hybrid Bat Algorithm with Harmony Search for Global Numerical Optimization
title_sort novel hybrid bat algorithm with harmony search for global numerical optimization
url http://dx.doi.org/10.1155/2013/696491
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