Using genetic Algorithm in Task scheduling for Multiprocessing System

In this work we use Genetic Algorithm for best section to implement many independent tasks on multiprocessor systems. The chromosome represented by numbers of integer value, every value represents one of the processors in the system, we use the simple crossover to generate the next population, and w...

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Main Authors: Asmaa Hammo, Ghosun Basheer, Muna Jawhar
Format: Article
Language:English
Published: Mosul University 2007-07-01
Series:Al-Rafidain Journal of Computer Sciences and Mathematics
Subjects:
Online Access:https://csmj.mosuljournals.com/article_164004_2c4e44f461df42fbdd6d735fc828748f.pdf
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author Asmaa Hammo
Ghosun Basheer
Muna Jawhar
author_facet Asmaa Hammo
Ghosun Basheer
Muna Jawhar
author_sort Asmaa Hammo
collection DOAJ
description In this work we use Genetic Algorithm for best section to implement many independent tasks on multiprocessor systems. The chromosome represented by numbers of integer value, every value represents one of the processors in the system, we use the simple crossover to generate the next population, and we us the mutation of type  partial gen for mutation  which has a good role to improve results of scheduling, the program written by matlab (6.5).The results, after a small number of iterations, were very good .
format Article
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institution Kabale University
issn 1815-4816
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language English
publishDate 2007-07-01
publisher Mosul University
record_format Article
series Al-Rafidain Journal of Computer Sciences and Mathematics
spelling doaj-art-14aa2b18ff3f41b1b7a3cfe8d57f2e022025-08-20T03:48:28ZengMosul UniversityAl-Rafidain Journal of Computer Sciences and Mathematics1815-48162311-79902007-07-0141819810.33899/csmj.2007.164004164004Using genetic Algorithm in Task scheduling for Multiprocessing SystemAsmaa Hammo0Ghosun Basheer1Muna Jawhar2College of Computer Sciences and Mathematics/University of MosulCollege of Computer Sciences and Mathematics University of Mosul, IraqCollege of Computer Sciences and Mathematics University of Mosul, IraqIn this work we use Genetic Algorithm for best section to implement many independent tasks on multiprocessor systems. The chromosome represented by numbers of integer value, every value represents one of the processors in the system, we use the simple crossover to generate the next population, and we us the mutation of type  partial gen for mutation  which has a good role to improve results of scheduling, the program written by matlab (6.5).The results, after a small number of iterations, were very good .https://csmj.mosuljournals.com/article_164004_2c4e44f461df42fbdd6d735fc828748f.pdfgenetic algorithmscheduling taskmultiprocessing
spellingShingle Asmaa Hammo
Ghosun Basheer
Muna Jawhar
Using genetic Algorithm in Task scheduling for Multiprocessing System
Al-Rafidain Journal of Computer Sciences and Mathematics
genetic algorithm
scheduling task
multiprocessing
title Using genetic Algorithm in Task scheduling for Multiprocessing System
title_full Using genetic Algorithm in Task scheduling for Multiprocessing System
title_fullStr Using genetic Algorithm in Task scheduling for Multiprocessing System
title_full_unstemmed Using genetic Algorithm in Task scheduling for Multiprocessing System
title_short Using genetic Algorithm in Task scheduling for Multiprocessing System
title_sort using genetic algorithm in task scheduling for multiprocessing system
topic genetic algorithm
scheduling task
multiprocessing
url https://csmj.mosuljournals.com/article_164004_2c4e44f461df42fbdd6d735fc828748f.pdf
work_keys_str_mv AT asmaahammo usinggeneticalgorithmintaskschedulingformultiprocessingsystem
AT ghosunbasheer usinggeneticalgorithmintaskschedulingformultiprocessingsystem
AT munajawhar usinggeneticalgorithmintaskschedulingformultiprocessingsystem