Constrained stochastic blackbox optimization using a progressive barrier and probabilistic estimates

DOI10.1007/s10107-022-01787-7OpenAlexW3105596848MaRDI QIDQ2687061

Sébastien Le Digabel, Michael Kokkolaras, Kwassi Joseph Dzahini

Publication date: 1 March 2023

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2011.04225

Mathematics Subject Classification ID

Nonlinear programming (90C30) Derivative-free methods and methods using generalized derivatives (90C56) Stochastic programming (90C15)

Uses Software

• OrthoMADS
• ASTRO-DF

Cites Work

• Unnamed Item
• Stochastic derivative-free optimization using a trust region framework
• Test examples for nonlinear programming codes
• Stochastic optimization using a trust-region method and random models
• Robust optimization of noisy blackbox problems using the mesh adaptive direct search algorithm
• Constrained Bayesian optimization with noisy experiments
• Stochastic Nelder-Mead simplex method -- a new globally convergent direct search method for simulation optimization
• Stochastic mesh adaptive direct search for blackbox optimization using probabilistic estimates
• Expected complexity analysis of stochastic direct-search
• Direct search based on probabilistic feasible descent for bound and linearly constrained problems
• Sequential approximate optimization using radial basis function network for engineering optimization
• Minimization of functions having Lipschitz continuous first partial derivatives
• A Direct Search Algorithm for Optimization with Noisy Function Evaluations
• Nonconvex Robust Optimization for Problems with Constraints
• Convergence of Trust-Region Methods Based on Probabilistic Models
• Response surface methodology with stochastic constraints for expensive simulation
• Parallel Space Decomposition of the Mesh Adaptive Direct Search Algorithm
• OrthoMADS: A Deterministic MADS Instance with Orthogonal Directions
• Introduction to Derivative-Free Optimization
• Generalized Directional Derivatives and Subgradients of Nonconvex Functions
• Nelder-Mead Simplex Modifications for Simulation Optimization
• ASTRO-DF: A Class of Adaptive Sampling Trust-Region Algorithms for Derivative-Free Stochastic Optimization
• Derivative-Free and Blackbox Optimization
• The Mesh Adaptive Direct Search Algorithm for Granular and Discrete Variables
• A Pattern Search Filter Method for Nonlinear Programming without Derivatives
• A Survey on Direct Search Methods for Blackbox Optimization and Their Applications
• Optimization of Stochastic Blackboxes with Adaptive Precision
• Benchmarking Derivative-Free Optimization Algorithms
• A Progressive Barrier for Derivative-Free Nonlinear Programming
• A Stochastic Line Search Method with Expected Complexity Analysis
• A pattern search and implicit filtering algorithm for solving linearly constrained minimization problems with noisy objective functions
• Mesh Adaptive Direct Search Algorithms for Constrained Optimization
• A Simplex Method for Function Minimization
• A Stochastic Approximation Method
• Probability
• A basic course in probability theory
• Benchmarking optimization software with performance profiles.