Parallel genetic algorithms on line topology of heterogeneous computing resources

This paper evaluates a parallel genetic algorithm (GA) on the line topology of heterogeneous computing resources. Evolution process of parallel GAs is investigated on two types of arrangements of heterogeneous computing resources: the ascending and descending order arrangement of computing capability. Their differences in chromosome variety, migration frequency and solution quality are investigated. The results in this paper can help to design parallel GAs in grid computing environments.

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