Department of Applied Mathematics & Physics, Kyoto Univiversity
Technical Report #99012 (June, 1999)
The proximal point algorithm with genuine superlinear convergence for the monotone complementarity problem
by Nobuo Yamashita and Masao Fukushima
In this paper, we consider
a proximal point algorithm (PPA) for solving
monotone nonlinear complementarity problems (NCP).
PPA generates a sequence by
solving subproblems that are regularizations of the original problem.
It is known that
PPA has global and superlinear convergence property
under appropriate criteria for approximate solutions of subproblems.
However, it is not always easy to solve subproblems or
to check those criteria.
In this paper, we adopt
the generalized Newton method proposed by De Luca, Facchinei and Kanzow
to solve subproblems and some NCP functions
to check the criteria.
Then we show that the PPA converges globally
provided that the solution set of the problem is nonempty.
Moreover, without assuming the local uniqueness of the solution,
we show that the rate of convergence is superlinear in a genuine sense,
provided that the limit point satisfies the strict complementarity