A least-squares-based method for a class of nonsmooth minimization problems with applications in plasticity

This paper introduces a globally convergent algorithm for solving a class of nonsmooth optimization problems, involving square roots of quadratic forms. The class includes in particular limit analysis problems in plasticity. The algorithm combines smoothing with successive approximation. The main computational effort in each iteration is solving a linear weighted least-squares problem. The convergence of the algorithm is proved and ana priori error estimate is obtained. Numerical results are presented for two limit analysis problems.The work of the first author was partially supported by NSF Grant DDM-89-96112. Parts of the work was done during his stay at the University of Bayreuth as a guest of the DFG. The work of the second author was supported in part by the Air Force Office of Scientific Research under contract AFOSR-88-0218 and by a National Science Foundation Grant ECS-8802239 at the University of Maryland, Baltimore County Campus.