A progressive barrier derivative-free trust-region algorithm for constrained optimization
From MaRDI portal
Publication:1616931
DOI10.1007/s10589-018-0020-4zbMath1409.90180OpenAlexW2517321039MaRDI QIDQ1616931
Sébastien Le Digabel, Andrew R. Conn, Charles Audet, Mathilde Peyrega
Publication date: 7 November 2018
Published in: Computational Optimization and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10589-018-0020-4
Nonlinear programming (90C30) Derivative-free methods and methods using generalized derivatives (90C56)
Related Items
A merit function approach for evolution strategies, A derivative-free optimization algorithm for the efficient minimization of functions obtained via statistical averaging
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A derivative-free algorithm for linearly constrained optimization problems
- On convergence analysis of a derivative-free trust region algorithm for constrained optimization with separable structure
- Inexact restoration method for nonlinear optimization without derivatives
- On fast trust region methods for quadratic models with linear constraints
- An inexact restoration derivative-free filter method for nonlinear programming
- Nonlinear programming without a penalty function or a filter
- Nonsmooth optimization through mesh adaptive direct search and variable neighborhood search
- Globalization strategies for mesh adaptive direct search
- Linear equalities in blackbox optimization
- A derivative-free trust-funnel method for equality-constrained nonlinear optimization
- Recent advances in trust region algorithms
- CUTEst: a constrained and unconstrained testing environment with safe threads for mathematical optimization
- Direct search methods for nonlinearly constrained optimization using filters and frames
- Numerical experience with a derivative-free trust-funnel method for nonlinear optimization problems with general nonlinear constraints
- Convergence of Trust-Region Methods Based on Probabilistic Models
- Algorithm 909
- Sequential Penalty Derivative-Free Methods for Nonlinear Constrained Optimization
- Reducing the Number of Function Evaluations in Mesh Adaptive Direct Search Algorithms
- A Globally Convergent Augmented Lagrangian Algorithm for Optimization with General Constraints and Simple Bounds
- A trust-region derivative-free algorithm for constrained optimization
- Implementing Generating Set Search Methods for Linearly Constrained Minimization
- Active Set Identification for Linearly Constrained Minimization Without Explicit Derivatives
- Introduction to Derivative-Free Optimization
- Analysis of Generalized Pattern Searches
- Trust Region Methods
- Derivative-Free and Blackbox Optimization
- A Pattern Search Filter Method for Nonlinear Programming without Derivatives
- Use of quadratic models with mesh-adaptive direct search for constrained black box optimization
- A Survey on Direct Search Methods for Blackbox Optimization and Their Applications
- A Derivative-Free Algorithm for Inequality Constrained Nonlinear Programming via Smoothing of an $\ell_\infty$ Penalty Function
- Benchmarking Derivative-Free Optimization Algorithms
- Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points
- A Progressive Barrier for Derivative-Free Nonlinear Programming
- Stationarity Results for Generating Set Search for Linearly Constrained Optimization
- Mesh Adaptive Direct Search Algorithms for Constrained Optimization
- Nonlinear programming without a penalty function.
- A sequential quadratic programming algorithm for equality-constrained optimization without derivatives