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:
Online Access: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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author Alshaikhli, Imad Fakhri Taha
Khalil, Ismail
author_facet Alshaikhli, Imad Fakhri Taha
Khalil, Ismail
author_sort Alshaikhli, Imad Fakhri Taha
building IIUM Repository
collection Online Access
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.
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publishDate 2011
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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
spellingShingle QA75 Electronic computers. Computer science
Alshaikhli, Imad Fakhri Taha
Khalil, Ismail
An improved genetic algorithm for solving the multiprocessor scheduling problem
title 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_short An improved genetic algorithm for solving the multiprocessor scheduling problem
title_sort improved genetic algorithm for solving the multiprocessor scheduling problem
topic QA75 Electronic computers. Computer science
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