American Institute of Mathematical Sciences

October  2011, 7(4): 1041-1055. doi: 10.3934/jimo.2011.7.1041

A trust-region filter-SQP method for mathematical programs with linear complementarity constraints

 1 Department of Applied Mathematics, Beijing University of Technology, Beijing 100124, China 2 Department of Applied Mathematics, Hebei University of Technology, Tianjin 300401, China

Received  October 2010 Revised  July 2011 Published  August 2011

A trust-region filter-SQP method for mathematical programs with linear complementarity constraints (MPLCCs) is presented. The method is similar to that proposed by Liu, Perakis and Sun [Computational Optimization and Applications, 34, 5-33, 2006] but it solves the trust-region quadratic programming subproblems at each iteration and uses the filter technique to promote the global convergence. As a result, the method here is more robust since it admits the use of Lagrangian Hessian information and its performance is not affected by any penalty parameter. The preliminary numerical results on test problems generated by the QPECgen generator show that the presented method is effective.
Citation: Chunlin Hao, Xinwei Liu. A trust-region filter-SQP method for mathematical programs with linear complementarity constraints. Journal of Industrial & Management Optimization, 2011, 7 (4) : 1041-1055. doi: 10.3934/jimo.2011.7.1041
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