Abstract
Genetic Algorithm has been hybridized with classical optimization methods. Hybridization has been done in three approaches, by using conjugate gradient algorithm for Fletcher and Reeves, second by using steepest descent method and lastly by creation of initial population for genetic algorithm from one of conjugate gradient method, the numerical results were encouraging.
