A Regularization Newton Method for Solving Nonlinear Complementarity Problems
Journal Article
·
· Applied Mathematics and Optimization
In this paper we construct a regularization Newton method for solving the nonlinear complementarity problem (NCP(F )) and analyze its convergence properties under the assumption that F is a P{sub 0} -function. We prove that every accumulation point of the sequence of iterates is a solution of NCP(F ) and that the sequence of iterates is bounded if the solution set of NCP(F ) is nonempty and bounded. Moreover, if F is a monotone and Lipschitz continuous function, we prove that the sequence of iterates is bounded if and only if the solution set of NCP(F ) is nonempty by setting t=1/2 , where t element of [1/2,1] is a parameter. If NCP(F) has a locally unique solution and satisfies a nonsingularity condition, then the convergence rate is superlinear (quadratic) without strict complementarity conditions. At each step, we only solve a linear system of equations. Numerical results are provided and further applications to other problems are discussed.
- OSTI ID:
- 21067537
- Journal Information:
- Applied Mathematics and Optimization, Journal Name: Applied Mathematics and Optimization Journal Issue: 3 Vol. 40; ISSN 0095-4616
- Country of Publication:
- United States
- Language:
- English
Similar Records
Solving convex (and linear) complementarity problems by projection methods (undamped Newton)
Newton's method for large bound-constrained optimization problems.
Convergence Properties of the Regularized Newton Method for the Unconstrained Nonconvex Optimization
Conference
·
Fri Dec 30 23:00:00 EST 1994
·
OSTI ID:36050
Newton's method for large bound-constrained optimization problems.
Journal Article
·
Thu Dec 31 23:00:00 EST 1998
· SIAM J. Optimization
·
OSTI ID:942618
Convergence Properties of the Regularized Newton Method for the Unconstrained Nonconvex Optimization
Journal Article
·
Sun Aug 15 00:00:00 EDT 2010
· Applied Mathematics and Optimization
·
OSTI ID:21480262