Adaptive Parallel Genetic Algorithm

We propose a parallel genetic algorithm architecture which parameters are adapted automatically during the search process. The parameters of the search algorithm as selection pressure, mutation rate and mutation step size (or even others) are not fixed during the search process, but they are adapted in time. For their determination a simple, but effective method is used. The algorithm is able to adjust its properties according the currently solved problem, which allows also an unexperienced user to use parallel genetic algorithms without the need to set up its configuration a-priori for solving particular (specific) problems.