A nonsmooth version of the univariate optimization algorithm for locating the nearest extremum (locating extremum in nonsmooth univariate optimization)
DOI10.2478/s11533-008-0039-3zbMath1155.65050OpenAlexW2141081541MaRDI QIDQ944053
Publication date: 12 September 2008
Published in: Central European Journal of Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.2478/s11533-008-0039-3
algorithmunconstrained optimizationnumerical examplessuperlinear convergenceNewton-type methodsemismooth functionlinear bounding functionUnivariate optimization
Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Methods of quasi-Newton type (90C53)
Cites Work
- Unnamed Item
- A class of exponential quadratically convergent iterative formulae for unconstrained optimization
- Global optimization of univariate Lipschitz functions. I: Survey and properties
- Secant methods for semismooth equations
- A Newton-type univariate optimization algorithm for locating the nearest extremum
- Superlinear convergence of smoothing quasi-Newton methods for nonsmooth equations
- On concepts of directional differentiability
- Newton's method for the nonlinear complementarity problem: a B- differentiable equation approach
- A nonsmooth version of Newton's method
- Test Problems for Lipschitz Univariate Global Optimization with Multiextremal Constraints
- Newton's Method for B-Differentiable Equations
- Optimization and nonsmooth analysis
- Semismooth and Semiconvex Functions in Constrained Optimization
- Trust Region Methods
- Two Methods for Solving Optimization Problems Arising in Electronic Measurements and Electrical Engineering
- A Characterization of Superlinear Convergence and Its Application to Quasi-Newton Methods
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