In this paper, we propose a new Genetic Algorithm involving a mechanism of Co-evolution. Our Coevolutionary Genetic Algorithm consists of two Genetic Algorithms (GAs): a traditional GA which searches for the optimal solutions for given problems, and another GA to search for effective schemata in the former GA. Also, we adopt binary coding, partial spaces in genetic space, and rotated partial spaces as the coding method for the individuals in the latter GA, namely, schemata for the former GA. Moreover, we discuss on the effectiveness of coding and fitness evaluation for our Coevolutionary Genetic Algorithm. Several computational results on function optimization problems confirm the effectiveness of our approach.
