On the convergence of grid-based methods for unconstrained optimization

The convergence of direct search methods for unconstrained minimization is examined in the case where the underlying method can be interpreted as a gr id or pattern search over successively refined meshes. An important aspect of the main convergence result is that translation, rotation, scaling, and shearing of the successive grids are allowed.