A new global optimizing method and fast converge algorithm for nonlinear systems

In this paper the authors present a new method of global search for optimizing in n-dimensional space. This method is suitable for a function that has many extremes and has one or more nondifferentiable components. Using the Powell and Sargent analytical search algorithm for local extremes reduces the number of evaluations and improves the speed of the algorithm's convergence. >