A power penalty method for a bounded nonlinear complementarity problem
Song Wang, Xiaoqi Yang · Optimization · 2014
We propose a novel power penalty approach to the bounded nonlinear complementarity problem (NCP) in which a reformulated NCP is approximated by a nonlinear equation containing a power penalty term. We show that the solution to the nonlinear equation converges to that of the bounded NCP at an exponential rate when the function is continuous and -monotone. A higher convergence rate is also obtained when the function becomes Lipschitz continuous and strongly monotone. Numerical results on discretized ‘double obstacle’ problems are presented to confirm the theoretical results.