Perbandingan Genetic Algorithm (GA) dan Particle Swarm Optimization (PSO) dalam Penentuan Solusi Sistem Persamaan Nonlinier

Abstract

Systems of nonlinear equations often appear in various fields of science and engi- neering, but their analytical solutions are difficult to find, so numerical methods are needed to solve them. The optimization method is very effective in finding solutions to nonlinear systems of equations, especially when traditional analytical and numerical methods are difficult to apply. Two popular optimization methods used for this purpose are Genetic Algorithm and Particle Swarm Optimization. This study aims to compare the effectiveness of GA and PSO in finding solutions to nonlinear systems of equations. To compare the two methods, the criteria used are the accuracy and convergence speed of both in finding solutions to nonlinear systems of equations. In this study, several examples of non-smooth nonlinear systems of equations are used for experimentation and comparison. The results provide insight into when and how to effectively use these two algorithms to solve nonlinear systems of equations as well as their potential combinations.