A derivative-free trust-region algorithm for composite nonsmooth optimization
DOI10.1007/s40314-014-0201-4zbMath1371.49014OpenAlexW2088650175MaRDI QIDQ2013620
Geovani Nunes Grapiglia, Jin Yun Yuan, Ya-Xiang Yuan
Publication date: 8 August 2017
Published in: Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s40314-014-0201-4
global convergencenonsmooth optimizationnonlinear programmingderivative-free optimizationworst-case complexitytrust-region methods
Analysis of algorithms and problem complexity (68Q25) Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Derivative-free methods and methods using generalized derivatives (90C56) Nonsmooth analysis (49J52) Set-valued and variational analysis (49J53) Numerical methods based on nonlinear programming (49M37) Implicit function theorems; global Newton methods on manifolds (58C15)
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- NOMAD
- On the convergence and worst-case complexity of trust-region and regularization methods for unconstrained optimization
- Derivative-free methods for nonlinear programming with general lower-level constraints
- Adaptive cubic regularisation methods for unconstrained optimization. II: Worst-case function- and derivative-evaluation complexity
- A smooth method for the finite minimax problem
- Global convergence of trust-region algorithms for convex constrained minimization without derivatives
- A trust region algorithm for minimization of locally Lipschitzian functions
- A trust region algorithm for nonsmooth optimization
- Constrained derivative-free optimization on thin domains
- Random gradient-free minimization of convex functions
- On the complexity of finding first-order critical points in constrained nonlinear optimization
- Optimization theory and methods. Nonlinear programming
- Smoothing and worst-case complexity for direct-search methods in nonsmooth optimization
- Inexact Restoration Method for Derivative-Free Optimization with Smooth Constraints
- On the Evaluation Complexity of Cubic Regularization Methods for Potentially Rank-Deficient Nonlinear Least-Squares Problems and Its Relevance to Constrained Nonlinear Optimization
- On the Oracle Complexity of First-Order and Derivative-Free Algorithms for Smooth Nonconvex Minimization
- Algorithm 909
- Self-Correcting Geometry in Model-Based Algorithms for Derivative-Free Unconstrained Optimization
- On the Evaluation Complexity of Composite Function Minimization with Applications to Nonconvex Nonlinear Programming
- The Cutting-Plane Method for Solving Convex Programs
- A trust-region derivative-free algorithm for constrained optimization
- Introduction to Derivative-Free Optimization
- On the global convergence of trust region algorithms for unconstrained minimization
- Conditions for convergence of trust region algorithms for nonsmooth optimization
- On the superlinear convergence of a trust region algorithm for nonsmooth optimization
- `` Direct Search Solution of Numerical and Statistical Problems
- A model algorithm for composite nondifferentiable optimization problems
- A superlinearly convergent algorithm for minimization without evaluating derivatives
- A Quasi-Newton Method with No Derivatives
- Function Minimization by Interpolation in a Data Table
- Benchmarking Derivative-Free Optimization Algorithms
- Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points
- Mesh Adaptive Direct Search Algorithms for Constrained Optimization
- A Simplex Method for Function Minimization
- A Modification of Davidon's Minimization Method to Accept Difference Approximations of Derivatives