Solving Nonlinear Equation Systems Using Evolutionary Algorithms

This paper proposes a new perspective for solving systems of nonlinear equations. A system of equations can be viewed as a multiobjective optimization problem: every equation represents an objective function whose goal is to minimize difference between the right and left term of the corresponding equation in the system. We used an evolutionary computation technique to solve the problem obtained by transforming the system of nonlinear equations into a multiobjective problem. Results obtained are compared with a very new technique [10] and also some standard techniques used for solving nonlinear equation systems. Empirical results illustrate that the proposed method is efficient.