Genetic algorithms are considered a search process used in computing to find exact or approximate solutions for optimization and search problems. There are also termed as global search heuristics. These techniques are inspired by evolutionary biologies such as inheritance mutation, selection, and cross-over. These algorithms provide a technique for programs to improve their parameters automatically. This article is an introduction to the genetic algorithm approach including various applications and describes the integration of the genetic algorithm with object-oriented programming approaches.                  Genetic algorithm is a probabilistic solving optimization problem that is modeled on a genetic evaluation process in biology and is focused on an effective algorithm to find a global optimum solution for many types of problems. This algorithm is extremely applicable in different artificial intelligence approaches as well as different basic approaches like object-oriented, robotics, and others in the future we shall concentrate on the development of hybrid approaches using genetic algorithms and an object-oriented technology