Superlinear Convergence of a Smooth Approximation Method for Mathematical Programs with Nonlinear Complementarity Constraints |
| |
Authors: | Fujian Duan Lin Fan |
| |
Affiliation: | College of Mathematics and Computational Science,Guilin University of Electronic Technology,Guilin,541004,China |
| |
Abstract: | Mathematical programs with complementarity constraints (MPCC) is an im-portant subclass of MPEC. It is a natural way to solve MPCC by constructing a suit-able approximation of the primal problem. In this paper, we propose a new smoothing method for MPCC by using the aggregation technique. A new SQP algorithm for solving the MPCC problem is presented. At each iteration, the master direction is computed by solving a quadratic program, and the revised direction for avoiding the Maratos effect is generated by an explicit formula. As the non-degeneracy condition holds and the smoothing parameter tends to zero, the proposed SQP algorithm converges globally to an S-stationary point of the MPEC problem, its convergence rate is superlinear. Some preliminary numerical results are reported. |
| |
Keywords: | Mathematical programs with complementarity constraints nonlinear complementarityconstraints aggregation technique S-stationary point global convergence super-linear conver-gence |
本文献已被 CNKI 维普 万方数据 等数据库收录! |
|