Ulbrich, MichaelUlbrich, StefanVicente, Luis N.2018-06-182018-06-182000-04Ulbrich, Michael, Ulbrich, Stefan and Vicente, Luis N.. "A Globally Convergent Primal-Dual Interior-Point Filter Method for Nonconvex Nonlinear Programming." (2000) <a href="https://hdl.handle.net/1911/101941">https://hdl.handle.net/1911/101941</a>.https://hdl.handle.net/1911/101941In this paper, the filter technique of Fletcher and Leyffer (1997) is used to globalize the primal-dual interior-point algorithm for nonlinear programming, avoiding the use of merit functions and the updating of penalty parameters. The new algorithm decomposes the primal-dual step obtained from the perturbed first-order necessary conditions into a normal and a tangential step, whose sizes are controlled by a trust-region type parameter. Each entry in the filter is a pair of coordinates: one resulting from feasibility and centrality, and associated with the normal step; the other resulting from optimality (complementarity and duality), and related with the tangential step. Global convergence to first-order critical points is proved for the new primal-dual interior-point filter algorithm.29 ppengTechnical reportTR00-12