Solving nonlinear equations system via an efficient genetic algorithm with symmetric and harmonious individuals

We present an efficient genetic algorithm as a general tool for solving optimum problems. As a specialized application this algorithm can be used to approximate a solution of a system of nonlinear equations on n-dimensional Euclidean space setting. The new idea involves the introduction of some pairs of symmetric and harmonious individuals for the generation of a genetic algorithm. The population diversity is maintained better this way. The elitist model is used to ensure the convergence. Simulation results show that the new method is indeed very effective.