Author/Authors :
ÖZTÜRK, Nihat Gazi Üniversitesi - Teknoloji Fakültesi - Elektrik Elektronik Mühendisliği Bölümü, Turkey , ÇELİK, Emre Gazi Üniversitesi - Teknoloji Fakültesi - Elektrik Elektronik Mühendisliği Bölümü, Turkey
Abstract :
In this study, genetic algorithms (GAs), which have been used heavily in the field of optimization recently, have been applied to non-polynomial equation solutions. GAs simulate the evolutionary process in computer environment for the solutions of problems and instead of improving a single solution as in other optimization methods, such as hill-climbing algorithm, simulated annealing, etc., a GA forms a population composed of many potential solutions. Unlike ant colony algorithm, when the optimization process ends up, the best individual in the population forms the solution to the problem. To test the suitability of the proposed method, four different non-linear functions are utilized and the test results are compared to the real solutions of each functions. The obtained results from this study, realized in MATLAB® 6.5 environment, reveal that the suggested method has a good performance in terms of the converged root values of test functions and number of iterations.
