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Hybrid ant colony system and genetic algorithm approach for scheduling of jobs in computational grid


Alobaedy, Mustafa Muwafak and Ku-Mahamud, Ku Ruhana (2015) Hybrid ant colony system and genetic algorithm approach for scheduling of jobs in computational grid. Research Journal of Applied Sciences, Engineering and Technology, 11 (7). pp. 806-816. ISSN 20407459

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Abstract

Metaheuristic algorithms have been used to solve scheduling problems in grid computing.However, stand-alone metaheuristic algorithms do not always show good performance in every problem instance. This study proposes a high level hybrid approach between ant colony system and genetic algorithm for job scheduling in grid computing.The proposed approach is based on a high level hybridization.The proposed hybrid approach is evaluated using the static benchmark problems known as ETC matrix.Experimental results show that the proposed hybridization between the two algorithms outperforms the stand-alone algorithms in terms of best and average makespan values.

Item Type: Article
Uncontrolled Keywords: Hybrid metaheuristic algorithm, job scheduling, static grid computing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Computing
Depositing User: Prof. Dr. Ku Ruhana Ku Mahamud
Date Deposited: 21 Feb 2016 07:04
Last Modified: 27 Apr 2016 01:05
URI: http://repo.uum.edu.my/id/eprint/17183

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