Trust-Region Methods for the Derivative-Free Optimization of Nonsmooth Black-Box Functions
From MaRDI portal
Publication:5203798
DOI10.1137/19M125772XzbMath1427.90298OpenAlexW2993741887WikidataQ126575651 ScholiaQ126575651MaRDI QIDQ5203798
Stefano Lucidi, Francesco Rinaldi, Luis Nunes Vicente, Giampaolo Liuzzi
Publication date: 9 December 2019
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1137/19m125772x
Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Derivative-free methods and methods using generalized derivatives (90C56)
Related Items
Full-low evaluation methods for derivative-free optimization, A discussion on variational analysis in derivative-free optimization, A clustering heuristic to improve a derivative-free algorithm for nonsmooth optimization, Conic formulation of QPCCs applied to truly sparse QPs, Manifold Sampling for Optimizing Nonsmooth Nonconvex Compositions, DFO-TRNS
Uses Software
Cites Work
- Unnamed Item
- DFN
- A derivative-free approximate gradient sampling algorithm for finite minimax problems
- Analysis of direct searches for discontinuous functions
- A trust region algorithm with a worst-case iteration complexity of \(\mathcal{O}(\epsilon ^{-3/2})\) for nonconvex optimization
- Computation of sparse low degree interpolating polynomials and their application to derivative-free optimization
- On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals
- Proximity control in bundle methods for convex nondifferentiable minimization
- Discrete gradient method: Derivative-free method for nonsmooth optimization
- Newton's method for convex programming and Tschebyscheff approximation
- A bundle-Newton method for nonsmooth unconstrained minimization
- New variants of bundle methods
- A derivative-free trust-region algorithm for composite nonsmooth optimization
- Methods of descent for nondifferentiable optimization
- A tilted cutting plane proximal bundle method for convex nondifferentiable optimization
- Trust-Region Methods Without Using Derivatives: Worst Case Complexity and the NonSmooth Case
- A Linesearch-Based Derivative-Free Approach for Nonsmooth Constrained Optimization
- Convergence of Trust-Region Methods Based on Probabilistic Models
- Algorithm 909
- A Nonderivative Version of the Gradient Sampling Algorithm for Nonsmooth Nonconvex Optimization
- A new trust region method for nonsmooth nonconvex optimization
- The Cutting-Plane Method for Solving Convex Programs
- Introduction to Derivative-Free Optimization
- Optimization and nonsmooth analysis
- A bundle type approach to the unconstrained minimization of convex nonsmooth functions
- A Version of the Bundle Idea for Minimizing a Nonsmooth Function: Conceptual Idea, Convergence Analysis, Numerical Results
- Trust Region Methods
- Manifold Sampling for Optimization of Nonconvex Functions That Are Piecewise Linear Compositions of Smooth Components
- Complexity and global rates of trust-region methods based on probabilistic models
- Generalized Bundle Methods
- Survey of Bundle Methods for Nonsmooth Optimization
- 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
- Manifold Sampling for $\ell_1$ Nonconvex Optimization
