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Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing

Hybrid metaheuristic algorithms have the ability to produce better solution than stand-alone approach and no algorithm could be concluded as the best algorithm for scheduling algorithm or in general, for combinatorial problems.This study presents the low and high level hybridization of ant colony sy...

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Main Authors: Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana
Format: Conference or Workshop Item
Language:English
Published: 2015
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://repo.uum.edu.my/15572/1/PID164.pdf
http://repo.uum.edu.my/15572/
http://www.icoci.cms.net.my/proceedings/2015/TOC.html
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spelling my.uum.repo.155722016-04-27T01:07:01Z http://repo.uum.edu.my/15572/ Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing Alobaedy, Mustafa Muwafak Ku-Mahamud, Ku Ruhana QA75 Electronic computers. Computer science Hybrid metaheuristic algorithms have the ability to produce better solution than stand-alone approach and no algorithm could be concluded as the best algorithm for scheduling algorithm or in general, for combinatorial problems.This study presents the low and high level hybridization of ant colony system and genetic algorithm in solving the job scheduling in grid computing.Two hybrid algorithms namely ACS(GA) as a low level and ACS+GA as a high level are proposed.The proposed algorithms were evaluated using static benchmarks problems known as expected time to compute model. Experimental results show that ant colony system algorithm performance is enhanced when hybridized with genetic algorithm specifically with high level hybridization. 2015 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/15572/1/PID164.pdf Alobaedy, Mustafa Muwafak and Ku-Mahamud, Ku Ruhana (2015) Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing. In: 5th International Conference on Computing and Informatics (ICOCI) 2015, 11-13 August 2015, Istanbul, Turkey. http://www.icoci.cms.net.my/proceedings/2015/TOC.html
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
Alobaedy, Mustafa Muwafak
Ku-Mahamud, Ku Ruhana
Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing
description Hybrid metaheuristic algorithms have the ability to produce better solution than stand-alone approach and no algorithm could be concluded as the best algorithm for scheduling algorithm or in general, for combinatorial problems.This study presents the low and high level hybridization of ant colony system and genetic algorithm in solving the job scheduling in grid computing.Two hybrid algorithms namely ACS(GA) as a low level and ACS+GA as a high level are proposed.The proposed algorithms were evaluated using static benchmarks problems known as expected time to compute model. Experimental results show that ant colony system algorithm performance is enhanced when hybridized with genetic algorithm specifically with high level hybridization.
format Conference or Workshop Item
author Alobaedy, Mustafa Muwafak
Ku-Mahamud, Ku Ruhana
author_facet Alobaedy, Mustafa Muwafak
Ku-Mahamud, Ku Ruhana
author_sort Alobaedy, Mustafa Muwafak
title Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing
title_short Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing
title_full Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing
title_fullStr Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing
title_full_unstemmed Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing
title_sort low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing
publishDate 2015
url http://repo.uum.edu.my/15572/1/PID164.pdf
http://repo.uum.edu.my/15572/
http://www.icoci.cms.net.my/proceedings/2015/TOC.html
_version_ 1644281751924637696
score 13.244368

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