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For the extended linear complementarity problem (ELCP), we establish a global error bound estimation for ELCP under milder condition. Based on this, we propose a smoothing algorithm for solving the problem. The algorithm is shown to be globally convergent and quadratically convergent rate without nondegenerate assumption. The result obtained in this paper extend the existing ones for the ELCP. Moreover, some numerical experimental results are presented, and indicate that the validity of the algorithm, as well as the rapid convergence of the method. [ABSTRACT FROM AUTHOR]

We first propose a new class of smoothing functions for the nonlinear complementarity function which contains the well-known Chen-Harker-Kanzow-Smale smoothing function and Huang-Han-Chen smoothing function as special cases, and then present a smoothing inexact Newton algorithm for the P nonlinear complementarity problem. The global convergence and local superlinear convergence are established. Preliminary numerical results indicate the feasibility and efficiency of the algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we propose an inexact smoothing continuation method for mathematical problem with complementarity constraints. Under suitable conditions, we establish the convergence of the proposed method by showing that any accumulation point of the generated sequence is a B -stationary point of the problem. [ABSTRACT FROM AUTHOR]