Mathematical programs with complementarity constraint (MPCC) are nonlinear optimization problem over a possibly non-convex and non-connected domain. Most of the numerical methods for nonlinear optimization problems relies on solving first-/second- order optimality conditions, which fail to hold for MPCC in general.
Some recent progress on MPCC-tailored optimality conditions, allow to build efficient relaxation methods starting from Kadrani et al in 2009 and followed by Kanzow & Schwarz in 2010.
We will discuss the weakest conditions needed to ensure convergence of these methods, present a new method with improved properties and present numerical comparison of these methods on a large number of test problems.
Talk from Archives
Numerical methods for Mathematical Programs with Complementarity Constraint
27.11.2017 16:45 - 17:45
Location:
HS 7 OMP1