@Article{NMTMA-3-367,
author = {Fujian Duan and Lin Fan},
title = {Superlinear Convergence of a Smooth Approximation Method for Mathematical Programs with Nonlinear Complementarity Constraints},
journal = {Numerical Mathematics: Theory, Methods and Applications},
year = {2010},
volume = {3},
number = {3},
pages = {367--386},
abstract = {<p style="text-align: justify;">Mathematical programs with complementarity
constraints (MPCC) is an important subclass of MPEC. It is a natural
way to solve MPCC by constructing a suitable approximation of the
primal problem. In this paper, we propose a new smoothing method for
MPCC by using the aggregation technique. A new SQP algorithm for
solving the MPCC problem is presented. At each iteration, the master
direction is computed by solving a quadratic program, and the
revised direction for avoiding the Maratos effect is generated by an
explicit formula. As the non-degeneracy condition holds and the
 smoothing parameter tends to zero, the proposed SQP algorithm
 converges globally to an S-stationary point of the MPEC problem, its
 convergence rate is superlinear. Some preliminary numerical results
 are reported.</p>},
issn = {2079-7338},
doi = {https://doi.org/10.4208/nmtma.2010.33.6},
url = {http://global-sci.org/intro/article_detail/nmtma/6004.html}
}