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A smoothing Newton method for mathematical programs constrained by parameterized quasi-variational inequalities

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Abstract

We consider a class of mathematical programs governed by parameterized quasi-variational inequalities (QVI). The necessary optimality conditions for the optimization problem with QVI constraints are reformulated as a system of nonsmooth equations under the linear independence constraint qualification and the strict slackness condition. A set of second order sufficient conditions for the mathematical program with parameterized QVI constraints are proposed, which are demonstrated to be sufficient for the second order growth condition. The strongly BD-regularity for the nonsmooth system of equations at a solution point is demonstrated under the second order sufficient conditions. The smoothing Newton method in Qi-Sun-Zhou [2000] is employed to solve this nonsmooth system and the quadratic convergence is guaranteed by the strongly BD-regularity. Numerical experiments are reported to show that the smoothing Newton method is very effective for solving this class of optimization problems.

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Authors and Affiliations

  1. School of Mathematical Sciences, Dalian University of Technology, Dalian, 116024, China

    Jia Wu & LiWei Zhang

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  1. Jia Wu
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  2. LiWei Zhang
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Correspondence to LiWei Zhang.

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Wu, J., Zhang, L. A smoothing Newton method for mathematical programs constrained by parameterized quasi-variational inequalities. Sci. China Math. 54, 1269–1286 (2011). https://doi.org/10.1007/s11425-011-4192-y

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  • DOI: https://doi.org/10.1007/s11425-011-4192-y

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