5 papers
Mesh-dependent iteration count growth in primal-dual active set strategies
Ioannis P. A. Papadopoulos, Michael Hintermüller
Primal-dual active set strategies (PDAS) are popular iterative solvers for mixed complementarity problems such as constrained optimization problems with pointwise inequality constr…
LeAP-SSN: A Semismooth Newton Method with Global Convergence Rates
Amal Alphonse, Pavel Dvurechensky, Ioannis P. A. Papadopoulos +1
We propose LeAP-SSN (Levenberg--Marquardt Adaptive Proximal Semismooth Newton method), a semismooth Newton-type method with a simple, parameter-free globalisation strategy that gua…
The latent variable proximal point algorithm for variational problems with inequality constraints
Jørgen S. Dokken, Patrick E. Farrell, Brendan Keith +2
The latent variable proximal point (LVPP) algorithm is a framework for solving infinite-dimensional variational problems with pointwise inequality constraints. The algorithm is a s…
Hierarchical proximal Galerkin: a fast -FEM solver for variational problems with pointwise inequality constraints
Ioannis P. A. Papadopoulos
We leverage the proximal Galerkin algorithm (Keith and Surowiec, Foundations of Computational Mathematics, 2024), a recently introduced mesh-independent algorithm, to obtain a high…
A Globalized Inexact Semismooth Newton Method for Nonsmooth Fixed-point Equations involving Variational Inequalities
Amal Alphonse, Constantin Christof, Michael Hintermüller +1
We develop a semismooth Newton framework for the numerical solution of fixed-point equations that are posed in Banach spaces. The framework is motivated by applications in the fiel…