Solution of non-polynomial equations based on genetic algorithm

28166

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.

322

Genetic algorithm , equation solution , optimization

Erciyes University Journal Of The Institute Of Science an‎d Technology

328

Erciyes University Journal Of The Institute Of Science an‎d Technology