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 grid 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.