New reformulation and feasible semismooth Newton method for a class of stochastic linear complementarity problems

DOI10.1016/j.amc.2011.04.060zbMath1232.65090OpenAlexW2062950692MaRDI QIDQ555370

Yakui Huang, Hong-Wei Liu, Xiang-Li Li

Publication date: 22 July 2011

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2011.04.060

zbMATH Keywords

numerical resultsconstrained minimizationfeasible semismooth Newton methodglobal and quadratic convergencestochastic linear complementarity problems

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Methods of quasi-Newton type (90C53) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33)

Related Items (5)

Smoothing projected Barzilai-Borwein method for constrained non-Lipschitz optimization ⋮ General fixed-point method for solving the linear complementarity problem ⋮ Expected residual minimization method for stochastic variational inequality problems with nonlinear perturbations ⋮ A Barzilai-Borwein type method for stochastic linear complementarity problems ⋮ Smoothing projected cyclic Barzilai–Borwein method for stochastic linear complementarity problems

Cites Work

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• Robust solution of monotone stochastic linear complementarity problems
• The \(SC^1\) 1property of an expected residual function arising from stochastic complementarity problems
• Feasible semismooth Newton method for a class of stochastic linear complementarity problems
• New improved error bounds for the linear complementarity problem
• A nonsmooth inexact Newton method for the solution of large-scale nonlinear complementarity problems
• Solution of monotone complementarity problems with locally Lipschitzian functions
• A feasible semismooth asymptotically Newton method for mixed complementarity problems
• Sample-path solution of stochastic variational inequalities
• A penalized Fischer-Burmeister NCP-function
• A regularization Newton method for solving nonlinear complementarity problems
• A nonsmooth version of Newton's method
• Stochastic $R_0$ Matrix Linear Complementarity Problems
• A special newton-type optimization method
• Engineering and Economic Applications of Complementarity Problems
• Convergence Analysis of Some Algorithms for Solving Nonsmooth Equations
• Finite-Dimensional Variational Inequalities and Complementarity Problems
• Expected Residual Minimization Method for Stochastic Linear Complementarity Problems
• New restricted NCP functions and their applications to stochastic NCP and stochastic MPEC
• New reformulations for stochastic nonlinear complementarity problems

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