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.

Keywords:

Hybrid metaheuristic algorithm, job scheduling, static grid computing,

References

Competing interests

The authors have no competing interests.

Open Access Policy

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Copyright

The authors have no competing interests.