A Robust SQP Method for Mathematical Programs with Linear Complementarity Constraints |
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| Authors: | Xinwei Liu Georgia Perakis Jie Sun |
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| Institution: | (1) Department of Applied Mathematics, Hebei University of Technology, Tianjin, China;(2) Singapore-MIT Alliance, National University of Singapore, Singapore;(3) Sloan School of Management, Massachusetts Institute of Technology, USA;(4) Department of Decision Sciences, National University of Singapore, Singapore;(5) National University of Singapore, Singapore |
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| Abstract: | The relationship between the mathematical program with linear complementarity constraints (MPLCC) and its inequality relaxation
is studied. Based on this relationship, a new sequential quadratic programming (SQP) method is presented for solving the MPLCC.
A certain SQP technique is introduced to deal with the possible infeasibility of quadratic programming subproblems. Global
convergence results are derived without assuming the linear independence constraint qualification for MPEC, the nondegeneracy
condition, and any feasibility condition of the quadratic programming subproblems. Preliminary numerical results are reported.
Research is partially supported by Singapore-MIT Alliance and School of Business, National University of Singapore. |
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| Keywords: | mathematical programs with equilibrium constraints sequential quadratic programming complementarity constraint qualification nondegeneracy |
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