Hybrid ant colony system and genetic algorithm approach for scheduling of jobs in computational grid
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 jo...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Maxwell Scientific Publication Corp.
2015
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/17183/1/9.pdf |
| Summary: | 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. |
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