eprintid: 8633
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/86/33
datestamp: 2023-11-09 16:20:33
lastmod: 2023-11-09 16:20:33
status_changed: 2023-11-09 16:13:08
type: article
metadata_visibility: show
creators_name: Ismail, I.
creators_name: Halim, A.H.
title: Comparative study of meta-heuristics optimization algorithm using benchmark function
ispublished: pub
note: cited By 16
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- A nd 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. © 2017 Institute of Advanced Engineering and Science.
date: 2017
publisher: Institute of Advanced Engineering and Science
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021102148&doi=10.11591%2fijece.v7i3.pp1643-1650&partnerID=40&md5=baea71ff36dd801108ea87b69a5a1a2a
id_number: 10.11591/ijece.v7i3.pp1643-1650
full_text_status: none
publication: International Journal of Electrical and Computer Engineering
volume: 7
number: 3
pagerange: 1643-1650
refereed: TRUE
issn: 20888708
citation:   Ismail, I. and Halim, A.H.  (2017) Comparative study of meta-heuristics optimization algorithm using benchmark function.  International Journal of Electrical and Computer Engineering, 7 (3).  pp. 1643-1650.  ISSN 20888708