Genetic algorithm and numerical methods for solving linear and nonlinear system of equations: a comparative study

摘要

The problem of solving linear and nonlinear system of equations is a largely useful issue of significant importance such as that it is presented on real-time applications. Different numerical methods such as fixed-point, Newton Raphson, bisection and secant methods, and or others, namely; evolutionary and computational methods are used to solve nonlinear system under optimizing the space and time complexity. Genetic Algorithm (GA) proved to be an efficient soft computing approach to solve many linear/non-linear system of equations. In this article, a comparison between different GAs and numerical methods for solving a system of equations are introduced. From the results, a novel approach is introduced which is inspired by using a modified GA to get the optimistic solution for the system which has no numerical solution and verified with the highest performance measures in solving complicated problems.