Centre based chromosomal representation of genetic algorithms to cluster new student

This paper is presented to explain application of Genetic Algorithms (GA) to cluster new students into several classes. It is very essential since good educational service for a large number of student needs clustering of them. There is no clustering method can handle it due to the capacity of each class. The supervised clustering method can only cluster students where number of class is predefined, but it cannot handle the class capacities. The proposed approach is GA which succeeded in solving difficult optimization problems. Since clustering method can be solved by minimizing the distance between each object in the cluster with the corresponding cluster center, we proposed GA with cluster centre based chromosomal representation. We developed it as software and evaluated it with random data. The result showed that the class generated by GA consists of more similar students than the class generated by traditional sorting method.