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Vibrant search mechanism for numerical optimization functions

Recently, various variants of evolutionary algorithms have been offered to optimize the exploration and exploitation abilities of the search mechanism.Some of these variants still suffer from slow convergence rates around the optimal solution. In this paper, a novel heuristic technique is introduced...

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Main Author: Shambour, Moh’d Khaled Yousef
Format: Article
Language:English
Published: Universiti Utara Malaysia 2018
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://repo.uum.edu.my/24944/1/JIICT%2017%204%202018%20679%E2%80%93702.pdf
http://repo.uum.edu.my/24944/
http://jict.uum.edu.my/index.php/current-issues-1#f
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spelling my.uum.repo.249442018-10-15T02:24:49Z http://repo.uum.edu.my/24944/ Vibrant search mechanism for numerical optimization functions Shambour, Moh’d Khaled Yousef QA75 Electronic computers. Computer science Recently, various variants of evolutionary algorithms have been offered to optimize the exploration and exploitation abilities of the search mechanism.Some of these variants still suffer from slow convergence rates around the optimal solution. In this paper, a novel heuristic technique is introduced to enhance the search capabilities of an algorithm, focusing on certain search spaces during evolution process. Then, employing a heuristic search mechanism that scans an entire space before determining the desired segment of that search space. The proposed method randomly updates the desired segment by monitoring the algorithm search performance levels on different search space divisions. The effectiveness of the proposed technique is assessed through harmony search algorithm (HSA). The performance of this mechanism is examined with several types of benchmark optimization functions, and the results are compared with those of the classic version and two variants of HSA. The experimental results demonstrate that the proposed technique achieves the lowest values (best results) in 80% of the non-shifted functions, whereas only 33.3% of total experimental cases are achieved within the shifted functions in a total of 30 problem dimensions. In 100 problem dimensions, 100% and 25% of the best results are reported for non-shifted and shifted functions, respectively. The results reveal that the proposed technique is able to orient the search mechanism toward desired segments of search space, which therefore significantly improves the overall search performance of HSA, especially for non-shifted optimization functions. Universiti Utara Malaysia 2018-10 Article PeerReviewed application/pdf en http://repo.uum.edu.my/24944/1/JIICT%2017%204%202018%20679%E2%80%93702.pdf Shambour, Moh’d Khaled Yousef (2018) Vibrant search mechanism for numerical optimization functions. Journal of ICT, 17 (4). pp. 679-702. ISSN 1675-414X http://jict.uum.edu.my/index.php/current-issues-1#f
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Shambour, Moh’d Khaled Yousef
Vibrant search mechanism for numerical optimization functions
description Recently, various variants of evolutionary algorithms have been offered to optimize the exploration and exploitation abilities of the search mechanism.Some of these variants still suffer from slow convergence rates around the optimal solution. In this paper, a novel heuristic technique is introduced to enhance the search capabilities of an algorithm, focusing on certain search spaces during evolution process. Then, employing a heuristic search mechanism that scans an entire space before determining the desired segment of that search space. The proposed method randomly updates the desired segment by monitoring the algorithm search performance levels on different search space divisions. The effectiveness of the proposed technique is assessed through harmony search algorithm (HSA). The performance of this mechanism is examined with several types of benchmark optimization functions, and the results are compared with those of the classic version and two variants of HSA. The experimental results demonstrate that the proposed technique achieves the lowest values (best results) in 80% of the non-shifted functions, whereas only 33.3% of total experimental cases are achieved within the shifted functions in a total of 30 problem dimensions. In 100 problem dimensions, 100% and 25% of the best results are reported for non-shifted and shifted functions, respectively. The results reveal that the proposed technique is able to orient the search mechanism toward desired segments of search space, which therefore significantly improves the overall search performance of HSA, especially for non-shifted optimization functions.
format Article
author Shambour, Moh’d Khaled Yousef
author_facet Shambour, Moh’d Khaled Yousef
author_sort Shambour, Moh’d Khaled Yousef
title Vibrant search mechanism for numerical optimization functions
title_short Vibrant search mechanism for numerical optimization functions
title_full Vibrant search mechanism for numerical optimization functions
title_fullStr Vibrant search mechanism for numerical optimization functions
title_full_unstemmed Vibrant search mechanism for numerical optimization functions
title_sort vibrant search mechanism for numerical optimization functions
publisher Universiti Utara Malaysia
publishDate 2018
url http://repo.uum.edu.my/24944/1/JIICT%2017%204%202018%20679%E2%80%93702.pdf
http://repo.uum.edu.my/24944/
http://jict.uum.edu.my/index.php/current-issues-1#f
_version_ 1644284184184750080
score 13.211869

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