  Nowadays, optimization problem have more application in all major but they
have problem in computation. Computation global point in continuous functions
have high calculation and this became clearer in large space .In this paper, we
proposed Sub- Dividing Genetic Method(SGM) that have less computation than
other method for achieving global points . This method userotation mutation and
crossover based sub-division method that sub diving method is used for minimize
search space and rotation mutation with crossover is used for finding global
optimal points. In experimental, SGM algorithm is implemented on De Jong
function. The numerical examples show that SGM is performed more optimal than
other methods such as Grefensstette, Random Value, and PNG.
