Discussion on searching capability of distributed genetic algorithm on the grid

The computational grid has become popular recently. Since the grid has the tremendous power, it is expected that the numerical optimization method like genetic algorithms (GA) performs well on the grid. In the former works, only the simple model of GA is applied on the grid. In this paper, when the distributed GA (DGA) is executed on the grid, the considerable issues and problems are discussed for the scalability, dynamic changes and heterogeneity. Through the numerical experiments, it is found that the DGA model has the following features on the grid; DGA has the scalability for searching the solutions with respect to the number of the resources and the results of the DGA are not influenced very much by the dynamic reduction of the number of resources. It is also addressed the affect of the asynchronous migration. As a result, the guideline how to implement the DGA on the grid is described.