An improved genetic algorithm for solving the multiprocessor scheduling problem

Multiprocessor Scheduling Problem (MSP) is an NP-complete optimization problem. The applications of this problem are numerous, but are, as suggested by the name of the problem, most strongly associated with the scheduling of computational tasks in a multiprocessor environment. Many methods and algor...

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Main Authors:	Alshaikhli, Imad Fakhri Taha, Khalil, Ismail
Format:	Article
Language:	English English
Published:	INSI Publications 2011
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://irep.iium.edu.my/8914/ http://irep.iium.edu.my/8914/ http://irep.iium.edu.my/8914/1/imad-fakhri.pdf http://irep.iium.edu.my/8914/4/An_improved_genetic.pdf

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recordtype	eprints
spelling	iium-89142012-02-10T07:04:12Z http://irep.iium.edu.my/8914/ An improved genetic algorithm for solving the multiprocessor scheduling problem Alshaikhli, Imad Fakhri Taha Khalil, Ismail QA75 Electronic computers. Computer science Multiprocessor Scheduling Problem (MSP) is an NP-complete optimization problem. The applications of this problem are numerous, but are, as suggested by the name of the problem, most strongly associated with the scheduling of computational tasks in a multiprocessor environment. Many methods and algorithms were suggested to solve this problem due to its importance. Genetic algorithms were among the suggested methods. In this research, sound improvements were done on one of the known papers [3]. Results show very good improvements in increasing the percentage of getting the exact solution as well as decreasing the number of generations needed to converge. INSI Publications 2011-12 Article PeerReviewed application/pdf en http://irep.iium.edu.my/8914/1/imad-fakhri.pdf application/pdf en http://irep.iium.edu.my/8914/4/An_improved_genetic.pdf Alshaikhli, Imad Fakhri Taha and Khalil, Ismail (2011) An improved genetic algorithm for solving the multiprocessor scheduling problem. Australian Journal of Basic and Applied Sciences. ISSN 1991-8178 (In Press) http://www.insipub.com/ajbas.html
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Alshaikhli, Imad Fakhri Taha Khalil, Ismail An improved genetic algorithm for solving the multiprocessor scheduling problem
description	Multiprocessor Scheduling Problem (MSP) is an NP-complete optimization problem. The applications of this problem are numerous, but are, as suggested by the name of the problem, most strongly associated with the scheduling of computational tasks in a multiprocessor environment. Many methods and algorithms were suggested to solve this problem due to its importance. Genetic algorithms were among the suggested methods. In this research, sound improvements were done on one of the known papers [3]. Results show very good improvements in increasing the percentage of getting the exact solution as well as decreasing the number of generations needed to converge.
format	Article
author	Alshaikhli, Imad Fakhri Taha Khalil, Ismail
author_facet	Alshaikhli, Imad Fakhri Taha Khalil, Ismail
author_sort	Alshaikhli, Imad Fakhri Taha
title	An improved genetic algorithm for solving the multiprocessor scheduling problem
title_short	An improved genetic algorithm for solving the multiprocessor scheduling problem
title_full	An improved genetic algorithm for solving the multiprocessor scheduling problem
title_fullStr	An improved genetic algorithm for solving the multiprocessor scheduling problem
title_full_unstemmed	An improved genetic algorithm for solving the multiprocessor scheduling problem
title_sort	improved genetic algorithm for solving the multiprocessor scheduling problem
publisher	INSI Publications
publishDate	2011
url	http://irep.iium.edu.my/8914/ http://irep.iium.edu.my/8914/ http://irep.iium.edu.my/8914/1/imad-fakhri.pdf http://irep.iium.edu.my/8914/4/An_improved_genetic.pdf
first_indexed	2023-09-18T20:18:43Z
last_indexed	2023-09-18T20:18:43Z
_version_	1777407962397016064

An improved genetic algorithm for solving the multiprocessor scheduling problem

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