Convergence of the suitable affine subspace method for finding the least distance to a simplex

A minimum-length vector is found for a simplex in a finite-dimensional Euclidean space. The algorithm of successive projections onto affine subspaces containing suitable subsimplices of the initial simplex is shown to have a globally higher-than-linear convergence rate. Results of numerical experiments are presented.