Solving global optimal problems by using a dynamical evolutionary algorithm

We introduce a new dynamical evolutionary algorithm and use it to solve global optimal problems. A brief theoretical explanation for this algorithm is obtained from statistical mechanics. The algorithm has been evaluated numerically using a wide set of test functions which are nonlinear, multimodal and multidimensional. Numerical results show that the algorithm has the potential to obtain a global optimum or more accurate solutions than other methods for hard problems.