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Comparative Study of Meta-heuristics Optimization Algorithm using Benchmark Function

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 7 No. 3 (2017)

DOI
10.11591/ijece.v7i3.pp1643-1650
ISSN
2088-8708, 2088-8708
Published
2017-06-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Meta-heuristics optimization is becoming a popular tool for solving numerous problems in real-world application due to the ability to overcome many shortcomings in traditional optimization. Despite of the good performance, there is limitation in some algorithms that deteriorates by certain degree of problem type. Therefore it is necessary to compare the performance of these algorithms with certain problem type. This paper compares 7 meta-heuristics optimization with 11 benchmark functions that exhibits certain difficulties and can be assumed as a simulation relevant to the real-world problems. The tested benchmark function has different type of problem such as modality, separability, discontinuity and surface effects with steep-drop global optimum, bowl- and plateau-typed function. Some of the proposed function has the combination of these problems, which might increase the difficulty level of search towards global optimum. The performance comparison includes computation time and convergence of global optimum.

Collaboration network of the authors

2 authors · 1 co-authorship link

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  • Universiti Teknologi Petronas
  • Different organisations
  • Same organisation
  • Affiliation unknown
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Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Comparative Study of Meta-heuristics Optimization Algorithm using Benchmark Function</dc:title><dc:creator>Ismail, I.</dc:creator><dc:creator>Halim, A. Hanif</dc:creator><dc:description>&lt;jats:p&gt;&amp;lt;span lang="EN-US"&amp;gt;Meta-heuristics optimization is becoming a popular tool for solving numerous problems in real-world application due to the ability to overcome many shortcomings in traditional optimization. Despite of the good performance, there is limitation in some algorithms that deteriorates by certain degree of problem type. Therefore it is necessary to compare the performance of these algorithms with certain problem type. This paper compares 7 meta-heuristics optimization with 11 benchmark functions that exhibits certain difficulties and can be assumed as a simulation relevant to the real-world problems. The tested benchmark function has different type of problem such as modality, &amp;lt;/span&amp;gt;&amp;lt;span lang="EN-MY"&amp;gt;separability&amp;lt;/span&amp;gt;&amp;lt;span lang="EN-US"&amp;gt;, discontinuity and surface effects with steep-drop global optimum, bowl- and plateau-typed function. Some of the proposed function has the combination of these problems, which might increase the difficulty level of search towards global optimum. The performance comparison includes computation time and convergence of global optimum.&amp;lt;/span&amp;gt;&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2017-06-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v7i3.pp1643-1650</dc:identifier><dc:identifier>10.11591/ijece.v7i3.pp1643-1650</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 7 No 3 (2017); 1643</dc:source><dc:source>2088-8708</dc:source><dc:source>2088-8708</dc:source><dc:relation>http://ijece.iaescore.com/index.php/IJECE/article/viewFile/6463/6544</dc:relation><dc:rights>http://creativecommons.org/licenses/by-nc/4.0</dc:rights></oai_dc:dc>