A new HMCR parameter of harmony search for better exploration

As a meta-heuristic algorithm, Harmony Search (HS) algorithm is a population-based meta-heuristics approach that is superior in solving diversified large scale optimization problems. Several studies have pointed that Harmony Search (HS) is an efficient and flexible tool to resolve optimization probl...

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Main Authors: Nur Farraliza, Mansor, Abas, Z.A, Rahman, A.F.N.A, Shibghatullah, A.S., Sidek, S
Format: Conference or Workshop Item
Language:English
Published: 2015
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Online Access:http://eprints.unisza.edu.my/556/1/FH03-FIK-16-05251.jpg
http://eprints.unisza.edu.my/556/
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spelling my-unisza-ir.5562020-10-25T04:20:12Z http://eprints.unisza.edu.my/556/ A new HMCR parameter of harmony search for better exploration Nur Farraliza, Mansor Abas, Z.A Rahman, A.F.N.A Shibghatullah, A.S. Sidek, S QA75 Electronic computers. Computer science QA76 Computer software As a meta-heuristic algorithm, Harmony Search (HS) algorithm is a population-based meta-heuristics approach that is superior in solving diversified large scale optimization problems. Several studies have pointed that Harmony Search (HS) is an efficient and flexible tool to resolve optimization problems in diversed areas of construction, engineering, robotics, telecommunication, health and energy. In this respect, the three main operators in HS, namely the Harmony Memory Consideration Rate (HMCR), Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing the local exploitation and the global exploration. These parameters influence the overall performance of HS algorithm, and therefore it is very crucial to fine turn them. However, when performing a local search, the harmony search algorithm can be easily trapped in the local optima. Therefore, there is a need to improve the fine tuning of the parameters. This research focuses on the HMCR parameter adjustment strategy using step function with combined Gaussian distribution function to enhance the global optimality of HS. The result of the study showed a better global optimum in comparison to the standard HS. 2015 Conference or Workshop Item NonPeerReviewed image en http://eprints.unisza.edu.my/556/1/FH03-FIK-16-05251.jpg Nur Farraliza, Mansor and Abas, Z.A and Rahman, A.F.N.A and Shibghatullah, A.S. and Sidek, S (2015) A new HMCR parameter of harmony search for better exploration. In: 2nd International Conference on Harmony Search Algorithm, ICHSA 2015, 19-21 August 2015, Seoul; South Korea.
institution Universiti Sultan Zainal Abidin
building UNISZA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sultan Zainal Abidin
content_source UNISZA Institutional Repository
url_provider https://eprints.unisza.edu.my/
language English
topic QA75 Electronic computers. Computer science
QA76 Computer software
spellingShingle QA75 Electronic computers. Computer science
QA76 Computer software
Nur Farraliza, Mansor
Abas, Z.A
Rahman, A.F.N.A
Shibghatullah, A.S.
Sidek, S
A new HMCR parameter of harmony search for better exploration
description As a meta-heuristic algorithm, Harmony Search (HS) algorithm is a population-based meta-heuristics approach that is superior in solving diversified large scale optimization problems. Several studies have pointed that Harmony Search (HS) is an efficient and flexible tool to resolve optimization problems in diversed areas of construction, engineering, robotics, telecommunication, health and energy. In this respect, the three main operators in HS, namely the Harmony Memory Consideration Rate (HMCR), Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing the local exploitation and the global exploration. These parameters influence the overall performance of HS algorithm, and therefore it is very crucial to fine turn them. However, when performing a local search, the harmony search algorithm can be easily trapped in the local optima. Therefore, there is a need to improve the fine tuning of the parameters. This research focuses on the HMCR parameter adjustment strategy using step function with combined Gaussian distribution function to enhance the global optimality of HS. The result of the study showed a better global optimum in comparison to the standard HS.
format Conference or Workshop Item
author Nur Farraliza, Mansor
Abas, Z.A
Rahman, A.F.N.A
Shibghatullah, A.S.
Sidek, S
author_facet Nur Farraliza, Mansor
Abas, Z.A
Rahman, A.F.N.A
Shibghatullah, A.S.
Sidek, S
author_sort Nur Farraliza, Mansor
title A new HMCR parameter of harmony search for better exploration
title_short A new HMCR parameter of harmony search for better exploration
title_full A new HMCR parameter of harmony search for better exploration
title_fullStr A new HMCR parameter of harmony search for better exploration
title_full_unstemmed A new HMCR parameter of harmony search for better exploration
title_sort new hmcr parameter of harmony search for better exploration
publishDate 2015
url http://eprints.unisza.edu.my/556/1/FH03-FIK-16-05251.jpg
http://eprints.unisza.edu.my/556/
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score 13.159267