Best Polynomial Harmony Search with Best β-Hill Climbing Algorithm

Harmony Search Algorithm (HSA) is an evolutionary algorithm which mimics the process of music improvisation to obtain a nice harmony. The algorithm has been successfully applied to solve optimization problems in different domains. A significant shortcoming of the algorithm is inadequate exploitation...

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Autores principales:	Abu Doush Iyad, Santos Eugene
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2020
Materias:	harmony search algorithm evolutionary algorithms hill climbing polynomial mutation β-hill climbing 68w50 68t20 90c59 Science Q Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/810a91e3814e4ae592c05825cdeade31
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spelling	oai:doaj.org-article:810a91e3814e4ae592c05825cdeade312021-12-05T14:10:51ZBest Polynomial Harmony Search with Best β-Hill Climbing Algorithm2191-026X10.1515/jisys-2019-0101https://doaj.org/article/810a91e3814e4ae592c05825cdeade312020-05-01T00:00:00Zhttps://doi.org/10.1515/jisys-2019-0101https://doaj.org/toc/2191-026XHarmony Search Algorithm (HSA) is an evolutionary algorithm which mimics the process of music improvisation to obtain a nice harmony. The algorithm has been successfully applied to solve optimization problems in different domains. A significant shortcoming of the algorithm is inadequate exploitation when trying to solve complex problems. The algorithm relies on three operators for performing improvisation: memory consideration, pitch adjustment, and random consideration. In order to improve algorithm efficiency, we use roulette wheel and tournament selection in memory consideration, replace the pitch adjustment and random consideration with a modified polynomial mutation, and enhance the obtained new harmony with a modified β-hill climbing algorithm. Such modification can help to maintain the diversity and enhance the convergence speed of the modified HS algorithm. β-hill climbing is a recently introduced local search algorithm that is able to effectively solve different optimization problems. β-hill climbing is utilized in the modified HS algorithm as a local search technique to improve the generated solution by HS. Two algorithms are proposed: the first one is called PHSβ–HC and the second one is called Imp. PHSβ–HC. The two algorithms are evaluated using 13 global optimization classical benchmark function with various ranges and complexities. The proposed algorithms are compared against five other HSA using the same test functions. Using Friedman test, the two proposed algorithms ranked 2nd (Imp. PHSβ–HC) and 3rd (PHSβ–HC). Furthermore, the two proposed algorithms are compared against four versions of particle swarm optimization (PSO). The results show that the proposed PHSβ–HC algorithm generates the best results for three test functions. In addition, the proposed Imp. PHSβ–HC algorithm is able to overcome the other algorithms for two test functions. Finally, the two proposed algorithms are compared with four variations of differential evolution (DE). The proposed PHSβ–HC algorithm produces the best results for three test functions, and the proposed Imp. PHSβ–HC algorithm outperforms the other algorithms for two test functions. In a nutshell, the two modified HSA are considered as an efficient extension to HSA which can be used to solve several optimization applications in the future.Abu Doush IyadSantos EugeneDe Gruyterarticleharmony search algorithmevolutionary algorithmshill climbingpolynomial mutationβ-hill climbing68w5068t2090c59ScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 1-17 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	harmony search algorithm evolutionary algorithms hill climbing polynomial mutation β-hill climbing 68w50 68t20 90c59 Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	harmony search algorithm evolutionary algorithms hill climbing polynomial mutation β-hill climbing 68w50 68t20 90c59 Science Q Electronic computers. Computer science QA75.5-76.95 Abu Doush Iyad Santos Eugene Best Polynomial Harmony Search with Best β-Hill Climbing Algorithm
description	Harmony Search Algorithm (HSA) is an evolutionary algorithm which mimics the process of music improvisation to obtain a nice harmony. The algorithm has been successfully applied to solve optimization problems in different domains. A significant shortcoming of the algorithm is inadequate exploitation when trying to solve complex problems. The algorithm relies on three operators for performing improvisation: memory consideration, pitch adjustment, and random consideration. In order to improve algorithm efficiency, we use roulette wheel and tournament selection in memory consideration, replace the pitch adjustment and random consideration with a modified polynomial mutation, and enhance the obtained new harmony with a modified β-hill climbing algorithm. Such modification can help to maintain the diversity and enhance the convergence speed of the modified HS algorithm. β-hill climbing is a recently introduced local search algorithm that is able to effectively solve different optimization problems. β-hill climbing is utilized in the modified HS algorithm as a local search technique to improve the generated solution by HS. Two algorithms are proposed: the first one is called PHSβ–HC and the second one is called Imp. PHSβ–HC. The two algorithms are evaluated using 13 global optimization classical benchmark function with various ranges and complexities. The proposed algorithms are compared against five other HSA using the same test functions. Using Friedman test, the two proposed algorithms ranked 2nd (Imp. PHSβ–HC) and 3rd (PHSβ–HC). Furthermore, the two proposed algorithms are compared against four versions of particle swarm optimization (PSO). The results show that the proposed PHSβ–HC algorithm generates the best results for three test functions. In addition, the proposed Imp. PHSβ–HC algorithm is able to overcome the other algorithms for two test functions. Finally, the two proposed algorithms are compared with four variations of differential evolution (DE). The proposed PHSβ–HC algorithm produces the best results for three test functions, and the proposed Imp. PHSβ–HC algorithm outperforms the other algorithms for two test functions. In a nutshell, the two modified HSA are considered as an efficient extension to HSA which can be used to solve several optimization applications in the future.
format	article
author	Abu Doush Iyad Santos Eugene
author_facet	Abu Doush Iyad Santos Eugene
author_sort	Abu Doush Iyad
title	Best Polynomial Harmony Search with Best β-Hill Climbing Algorithm
title_short	Best Polynomial Harmony Search with Best β-Hill Climbing Algorithm
title_full	Best Polynomial Harmony Search with Best β-Hill Climbing Algorithm
title_fullStr	Best Polynomial Harmony Search with Best β-Hill Climbing Algorithm
title_full_unstemmed	Best Polynomial Harmony Search with Best β-Hill Climbing Algorithm
title_sort	best polynomial harmony search with best β-hill climbing algorithm
publisher	De Gruyter
publishDate	2020
url	https://doaj.org/article/810a91e3814e4ae592c05825cdeade31
work_keys_str_mv	AT abudoushiyad bestpolynomialharmonysearchwithbestbhillclimbingalgorithm AT santoseugene bestpolynomialharmonysearchwithbestbhillclimbingalgorithm
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Best Polynomial Harmony Search with Best β-Hill Climbing Algorithm

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