An inexact semismooth Newton SAA-based algorithm for stochastic nonsmooth SOC complementarity problems with application to a stochastic power flow programming problem
DOI10.1016/J.CAM.2024.116361MaRDI QIDQ6664852
Pin-Bo Chen, Zhen-Ping Yang, Guihua Lin
Publication date: 16 January 2025
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
convergence analysissample average approximationinexact semismooth Newton algorithmstochastic nonsmooth second-order cone complementarity problems
Nonlinear programming (90C30) Nonsmooth analysis (49J52) Stochastic programming (90C15) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33)
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- A smoothing Broyden-like method with a nonmonotone derivative-free line search for nonlinear complementarity problems
- A smoothing Newton method with Fischer-Burmeister function for second-order cone complementarity problems
- Generalized Hessian matrix and second-order optimality conditions for problems with \(C^{1,1}\) data
- Smoothing sample average approximation method for solving stochastic second-order-cone complementarity problems
- A new model for solving stochastic second-order cone complementarity problem and its convergence analysis
- A damped Gauss-Newton method for the second-order cone complementarity problem
- An \(R\)-linearly convergent derivative-free algorithm for nonlinear complementarity problems based on the generalized Fischer-Burmeister merit function
- The semismooth-related properties of a merit function and a descent method for the nonlinear complementarity problem
- Superlinearly convergent approximate Newton methods for LC\(^ 1\) optimization problems
- A nonsmooth inexact Newton method for the solution of large-scale nonlinear complementarity problems
- Solution of monotone complementarity problems with locally Lipschitzian functions
- Globally convergent inexact quasi-Newton methods for solving nonlinear systems
- Stochastic second-order-cone complementarity problems: expected residual minimization formulation and its applications
- Expected residual minimization formulation for a class of stochastic linear second-order cone complementarity problems
- Sample average approximation for the continuous type principal-agent problem
- A new smoothing conjugate gradient method for solving nonlinear nonsmooth complementarity problems
- Complementarity functions and numerical experiments on some smoothing Newton methods for second-order-cone complementarity problems
- Smoothing Newton method for nonsmooth second-order cone complementarity problems with application to electric power markets
- On rates of convergence for sample average approximations in the almost sure sense and in mean
- Modified Jacobian smoothing method for nonsmooth complementarity problems
- A nonsmooth version of Newton's method
- Infinite dimensional generalized Jacobian: properties and calculus rules
- Strong semismoothness of the Fischer-Burmeister SDC and SOC complementarity functions
- Unconstrained minimization approaches to nonlinear complementarity problems
- Smoothing functions for second-order-cone complementarity problems
- Exact Convex Relaxation of Optimal Power Flow in Radial Networks
- Nonsmooth Equations: Motivation and Algorithms
- Optimization and nonsmooth analysis
- On second-order sufficient optimality conditions for c 1,1-optimization problems
- Generalized second-order derivatives and optimality conditions
- Convergence Analysis of Some Algorithms for Solving Nonsmooth Equations
- Global Convergence Analysis of the Generalized Newton and Gauss-Newton Methods of the Fischer-Burmeister Equation for the Complementarity Problem
- Model-Based Derivative-Free Methods for Convex-Constrained Optimization
- General Feasibility Bounds for Sample Average Approximation via Vapnik--Chervonenkis Dimension
- Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization
- A Combined Smoothing and Regularization Method for Monotone Second-Order Cone Complementarity Problems
- Expected Value and Sample Average Approximation Method for Solving Stochastic Second-Order Cone Complementarity Problems
- Moderate Deviations and Invariance Principles for Sample Average Approximations
This page was built for publication: An inexact semismooth Newton SAA-based algorithm for stochastic nonsmooth SOC complementarity problems with application to a stochastic power flow programming problem
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6664852)