AN EXACT PENALTY METHOD WITH REDUCED HESSIAN UPDATES FOR SOLVING CONSTRAINED OPTIMIZATION PROBLEMS

An algorithm using an exact penalty function and reduced Hessian updates for solving nonlinear optimization problems is described. A particular implementation of the algorithm and its testing with test problems from the literature is reported. The computational results show a superlinear rate of convergence and propose the algorithm as practical and competitive.