Experimental evaluation of a parallel genetic algorithm on line topology of heterogeneous computing resources

The paper investigates how the arrangement of heterogeneous computing resources affects evolution progress in a parallel genetic algorithm. This analysis is based on two types of computing groups, one sorted in ascending order and another one in descending order of computing capability. The results can help to design an efficient parallel genetic algorithm in grid computing environments.