@article{KanzowRaharjaSchwartz2021,
  author    = {Kanzow, Christian and Raharja, Andreas B. and Schwartz, Alexandra},
  title     = {An Augmented Lagrangian Method for Cardinality-Constrained Optimization Problems},
  series = {Journal of Optimization Theory and Applications},
  volume    = {189},
  journal   = {Journal of Optimization Theory and Applications},
  number    = {3},
  issn      = {1573-2878},
  doi       = {10.1007/s10957-021-01854-7},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-269166},
  pages     = {793-813},
  year      = {2021},
  abstract  = {A reformulation of cardinality-constrained optimization problems into continuous nonlinear optimization problems with an orthogonality-type constraint has gained some popularity during the last few years. Due to the special structure of the constraints, the reformulation violates many standard assumptions and therefore is often solved using specialized algorithms. In contrast to this, we investigate the viability of using a standard safeguarded multiplier penalty method without any problem-tailored modifications to solve the reformulated problem. We prove global convergence towards an (essentially strongly) stationary point under a suitable problem-tailored quasinormality constraint qualification. Numerical experiments illustrating the performance of the method in comparison to regularization-based approaches are provided.},
  language  = {en}
}
@phdthesis{Petra2006,
  author    = {Petra, Stefania},
  title     = {Semismooth least squares methods for complementarity problems},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-18660},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2006},
  abstract  = {This thesis is concerned with numerical methods for solving nonlinear and mixed complementarity problems. Such problems arise from a variety of applications such as equilibria models of economics, contact and structural mechanics problems, obstacle problems, discrete-time optimal control problems etc. In this thesis we present a new formulation of nonlinear and mixed complementarity problems based on the Fischer-Burmeister function approach. Unlike traditional reformulations, our approach leads to an over-determined system of nonlinear equations. This has the advantage that certain drawbacks of the Fischer-Burmeister approach are avoided. Among other favorable properties of the new formulation, the natural merit function turns out to be differentiable. To solve the arising over-determined system we use a nonsmooth damped Levenberg-Marquardt-type method and investigate its convergence properties. Under mild assumptions, it can be shown that the global and local fast convergence results are similar to some of the better equation-based method. Moreover, the new method turns out to be significantly more robust than the corresponding equation-based method. For the case of large complementarity problems, however, the performance of this method suffers from the need for solving the arising linear least squares problem exactly at each iteration. Therefore, we suggest a modified version which allows inexact solutions of the least squares problems by using an appropriate iterative solver. Under certain assumptions, the favorable convergence properties of the original method are preserved. As an alternative method for mixed complementarity problems, we consider a box constrained least squares formulation along with a projected Levenberg-Marquardt-type method. To globalize this method, trust region strategies are proposed. Several ingredients are used to improve this approach: affine scaling matrices and multi-dimensional filter techniques. Global convergence results as well as local superlinear/quadratic convergence are shown under appropriate assumptions. Combining the advantages of the new methods, a new software for solving mixed complementarity problems is presented.},
  subject      = {Komplementarit{\"a}tsproblem},
  language  = {en}
}