| _version_ |
1860799644617932800
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| building |
INTELEK Repository
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| collection |
Online Access
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| collectionurl |
https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2016-01-12 12:27:46
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| eventvenue |
Seoul, South Korea
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| format |
Restricted Document
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| id |
6820
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| institution |
UniSZA
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| originalfilename |
1154-01-FH03-FIK-16-04930.jpg
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| person |
norman
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| recordtype |
oai_dc
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| resourceurl |
https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6820
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| spelling |
6820 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6820 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper image/jpeg inches 96 96 norman 768 1423 04 04 2016-01-12 12:27:46 1423x768 1154-01-FH03-FIK-16-04930.jpg UniSZA Private Access 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 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. 2nd International Conference on Harmony Search Algorithm, ICHSA 2015 Seoul, South Korea
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| spellingShingle |
A new HMCR parameter of harmony search for better exploration
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| summary |
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.
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| title |
A new HMCR parameter of harmony search for better exploration
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| title_full |
A new HMCR parameter of harmony search for better exploration
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| 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
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| title_short |
A new HMCR parameter of harmony search for better exploration
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| title_sort |
new hmcr parameter of harmony search for better exploration
|