On the global convergence of derivative-free methods for unconstrained optimization

In this paper, starting from the study of the common elements that globally convergent direct search methods share,a general convergence theory is established for unconstrained minimization methods employing only function values. The introduced convergence conditions are useful to develop and analyse new derivative free algorithms with guaranteed global convergence. As examples, we describe three new algorithms which combine pattern and line search approaches.