Approximating Clarke's subgradients of semismooth functions by divided differences
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Publication:877273
DOI10.1007/s11075-007-9069-3zbMath1133.65043OpenAlexW1982706353MaRDI QIDQ877273
Rahmo El-Desouky, Marcin Studniarski
Publication date: 19 April 2007
Published in: Numerical Algorithms (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11075-007-9069-3
algorithmconvergencenumerical examplesnondifferentiable functionsClarke's subgradientssemismooth functions
Numerical optimization and variational techniques (65K10) Optimality conditions and duality in mathematical programming (90C46) Nonsmooth analysis (49J52)
Cites Work
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- A mesh-independence result for semismooth Newton methods.
- An algorithm for calculating one subgradient of a convex function of two variables
- A nonsmooth version of Newton's method
- An approximate Newton method for non-smooth equations with finite max functions
- Constrained optimal control of Navier--Stokes flow by semismooth Newton methods
- Optimization and nonsmooth analysis
- Second-Order Necessary Conditions in Constrained Semismooth Optimization
- Semismooth and Semiconvex Functions in Constrained Optimization
- An Algorithm for Constrained Optimization with Semismooth Functions
- A method for minimizing convex functions based on continuous approximations to the subdifferential
- Semismooth Newton Methods for Operator Equations in Function Spaces
- Smoothing Methods and Semismooth Methods for Nondifferentiable Operator Equations
- Convergence Analysis of Some Algorithms for Solving Nonsmooth Equations
- Finite-Dimensional Variational Inequalities and Complementarity Problems
- A SQP-Semismooth Newton-type Algorithm applied to Control of the instationary Navier--Stokes System Subject to Control Constraints
- Convex Analysis
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