Global Asynchronous Distributed Interactive Genetic Algorithm

We have already proposed Parallel Distributed Interactive Genetic Algorithm(PDIGA) that enables Interactive Genetic Algorithm (IGA) to be done at the same time by two or more people. In PDIGA, the synchronization of the generations is necessary among the subpopulations or users. Therefore, PDIGA is not appropriate for the situation with a large number of people in separate areas. In this paper, we propose Global Asynchronous Distributed Interactive Genetic Algorithm (GADIGA) as an algorithm for creating better design solutions with many people without synchronization. It is found that the asynchronous evolution is effective for making satisfying design solutions with the use of a database of elite individuals. Moreover, it is found that the users can generate more excellent design solutions by repeating the design process because better elite solutions are accumulated in the elite database. For two groups with different sensibilities, it is found that the exchange of design solutions between the groups is less than the one in the groups, but the exchange between the groups plays an important role. From the experimental results, GADIGA is found to be effective for creating better design solutions with many people in separate areas.