Genetic algorithm based optimization for system of nonlinear equations

This work explores a perspective for solving system of nonlinear equations which is an eminent problem in all scientific disciplines. An evolutionary computational technique is used to handle the nonlinear system of equations by converting it into a multi-objective optimization problem. A new fitness function has been proposed, the parameters have been chosen by prior empirical analysis. To validate the performance of the proposed methodology, sensitivity analysis has been carried out by varying the parameters of Genetic algorithm. The results obtained by new approach are quite encouraging and are also compared with other existing work.