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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my.iium.irep.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 REM 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 |
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QA75 Electronic computers. Computer science Alshaikhli, Imad Fakhri Taha Khalil, Ismail An improved genetic algorithm for solving the multiprocessor scheduling problem |
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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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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/8914/1/imad-fakhri.pdf http://irep.iium.edu.my/8914/4/An_improved_genetic.pdf http://irep.iium.edu.my/8914/ http://www.insipub.com/ajbas.html |
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1643606209648918528 |
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13.159267 |