A discussion on variational analysis in derivative-free optimization

DOI10.1007/s11228-020-00556-yzbMath1473.49019OpenAlexW3088043574MaRDI QIDQ829491

Warren L. Hare

Publication date: 6 May 2021

Published in: Set-Valued and Variational Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11228-020-00556-y

zbMATH Keywords

variational analysisderivative-free optimizationmodel-based methodsdirect-search methodorder-\(N\) accuracy

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Derivative-free methods and methods using generalized derivatives (90C56) Nonsmooth analysis (49J52)

Related Items (1)

A derivative-free trust-region algorithm with copula-based models for probability maximization problems

Uses Software

• CONDOR
• DFO
• BOBYQA
• COBYLA2
• GradSamp
• DGM
• MultiMin
• UOBYQA
• ORBIT
• Boosters
• ASTRO-DF
• MOIF
• DFO-TRNS

Cites Work

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• A derivative-free approximate gradient sampling algorithm for finite minimax problems
• CONDOR, a new parallel, constrained extension of Powell's UOBYQA algorithm: Experimental results and comparison with the DFO algorithm
• Parallel radial basis function methods for the global optimization of expensive functions
• Nonsmooth optimization through mesh adaptive direct search and variable neighborhood search
• Discrete gradient method: Derivative-free method for nonsmooth optimization
• Globalization strategies for mesh adaptive direct search
• On trust region methods for unconstrained minimization without derivatives
• Mesh-based Nelder-Mead algorithm for inequality constrained optimization
• Stochastic optimization using a trust-region method and random models
• Robust optimization of noisy blackbox problems using the mesh adaptive direct search algorithm
• Compositions of convex functions and fully linear models
• On the construction of quadratic models for derivative-free trust-region algorithms
• An implicit filtering algorithm for derivative-free multiobjective optimization with box constraints
• Efficient solution of quadratically constrained quadratic subproblems within the mesh adaptive direct search algorithm
• GOSH: derivative-free global optimization using multi-dimensional space-filling curves
• UOBYQA: unconstrained optimization by quadratic approximation
• Least Frobenius norm updating of quadratic models that satisfy interpolation conditions
• Derivative-free optimization via proximal point methods
• A mesh adaptive direct search algorithm for multiobjective optimization
• Derivative-free robust optimization by outer approximations
• Monotonic grey box direct search optimization
• The calculus of simplex gradients
• On the properties of positive spanning sets and positive bases
• Derivative-free optimization: a review of algorithms and comparison of software implementations
• Algorithmic construction of the subdifferential from directional derivatives
• Efficient calculation of regular simplex gradients
• Convergence results for generalized pattern search algorithms are tight
• Global Convergence of Radial Basis Function Trust Region Derivative-Free Algorithms
• Direct Multisearch for Multiobjective Optimization
• On the Convergence of Pattern Search Algorithms
• Reducing the Number of Function Evaluations in Mesh Adaptive Direct Search Algorithms
• Geometry of sample sets in derivative-free optimization: polynomial regression and underdetermined interpolation
• Introduction to Derivative-Free Optimization
• ORBIT: Optimization by Radial Basis Function Interpolation in Trust-Regions
• `` Direct Search Solution of Numerical and Statistical Problems
• A superlinearly convergent algorithm for minimization without evaluating derivatives
• Analysis of Generalized Pattern Searches
• Manifold Sampling for Optimization of Nonconvex Functions That Are Piecewise Linear Compositions of Smooth Components
• ASTRO-DF: A Class of Adaptive Sampling Trust-Region Algorithms for Derivative-Free Stochastic Optimization
• Derivative-Free and Blackbox Optimization
• Derivative-Free Optimization of Noisy Functions via Quasi-Newton Methods
• The Mesh Adaptive Direct Search Algorithm for Granular and Discrete Variables
• Optimization Methods for Large-Scale Machine Learning
• A derivative-free 𝒱𝒰-algorithm for convex finite-max problems
• Surrogate Optimization of Computationally Expensive Black-Box Problems with Hidden Constraints
• Adaptive Interpolation Strategies in Derivative-Free Optimization: a case study
• Trust-Region Methods for the Derivative-Free Optimization of Nonsmooth Black-Box Functions
• A Stochastic Line Search Method with Expected Complexity Analysis
• Derivative-free optimization methods
• A Robust Gradient Sampling Algorithm for Nonsmooth, Nonconvex Optimization
• Precision Control for Generalized Pattern Search Algorithms with Adaptive Precision Function Evaluations
• Mesh Adaptive Direct Search Algorithms for Constrained Optimization
• Manifold Sampling for $\ell_1$ Nonconvex Optimization
• A Simplex Method for Function Minimization
• Calculus Identities for Generalized Simplex Gradients: Rules and Applications
• A proximal bundle method for nonsmooth nonconvex functions with inexact information

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