A successive quadratic programming method for a class of constrained nonsmooth optimization problems
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Publication:1174457
DOI10.1007/BF01588789zbMath0735.90062OpenAlexW2049068112MaRDI QIDQ1174457
Publication date: 25 June 1992
Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/bf01588789
line searchexact penalizationapproximating Kuhn-Tucker pointsconstrained nonsmooth optimizationiterative cutting-plane type approach
Convex programming (90C25) Nonlinear programming (90C30) Quadratic programming (90C20) Nonsmooth analysis (49J52) Computational methods for problems pertaining to operations research and mathematical programming (90-08)
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Cites Work
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- Some remarks on the construction of higher order algorithms in convex optimization
- A method for minimizing the sum of a convex function and a continuously differentiable function
- An algorithm for composite nonsmooth optimization problems
- A constraint linearization method for nondifferentiable convex minimization
- A minimization method for the sum of a convex function and a continuously differentiable function
- Strong uniqueness: A far-reaching criterion for the convergence analysis of iterative procedures
- Truncated-Newton algorithms for large-scale unconstrained optimization
- Calculus Rules on the Approximate Second-Order Directional Derivative of a Convex Function
- Limiting behaviour of the approximate first order and second order directional derivatives for a convex function
- A descent algorithm for nonsmooth convex optimization
- Local properties of algorithms for minimizing nonsmooth composite functions
- Optimization and nonsmooth analysis
- An Efficient Trust Region Algorithm for Minimizing Nondifferentiable Composite Functions
- A generalized proximal point algorithm for certain non-convex minimization problems
- Optimality conditions for piecewise smooth functions
- Submonotone mappings and the proximal point algorithm
- ε-Optimal solutions in nondifferentiable convex programming and some related questions
- On the Extension of Constrained Optimization Algorithms from Differentiable to Nondifferentiable Problems
- Monotone Operators and the Proximal Point Algorithm
- Numerical methods for nondifferentiable convex optimization
- An Exact Penalty Function Algorithm for Non-smooth Convex Constrained Minimization Problems
- Convex Analysis
