A smoothing conic trust region filter method for the nonlinear complementarity problem (Q1023330)

In this paper, a new conic trust region filter method is proposed to solve the nonlinear complementarity problem by combining the advantage of a trust region based on the conic model and filter method. The author shows that every accumulation point of the sequence generated by the algorithm is a solution of the nonlinear complementarity problem. The global convergence is proved. Under a nonsingularity condition, the superlinear convergence of the algorithm is established in the absence of strict complementarity.