On a method of random search for unconstrained optimization

In this paper a random search algorithm for minimizing $f(x)$ in the Euclidean space $E^n$ is described. On the base of numerical solution of some standard test problems, test problems, the efficiency of the methods is compared with that of several random and deterministic derivative-free methods of nonlinear programming.