We propose a new perspective for solving systems of nonlinear equations by viewing them as a multiobjective optimization problem where every equation represents an objective function whose goal is to minimize the difference between the right- and left-hand side of the corresponding equation of the system. An evolutionary computation technique is suggested to solve the problem obtained by transforming the system into a multiobjective optimization problem. Results obtained are compared with some of the well-established techniques used for solving nonlinear equation systems.