A derivative-free optimization algorithm for the efficient minimization of functions obtained via statistical averaging

DOI10.1007/s10589-020-00172-4zbMath1433.90193arXiv1910.12393OpenAlexW3004639768MaRDI QIDQ1986101

Ryan Alimo, Thomas R. Bewley, Pooriya Beyhaghi

Publication date: 7 April 2020

Published in: Computational Optimization and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1910.12393

zbMATH Keywords

Delaunay triangulationderivative-free optimizationstatistical averaging

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26) Derivative-free methods and methods using generalized derivatives (90C56)

Related Items (2)

Loss functions for finite sets ⋮ Optimization of Stochastic Blackboxes with Adaptive Precision

Uses Software

• longmemo
• Spearmint

Cites Work

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• Exploring or reducing noise? A global optimization algorithm in the presence of noise
• Delaunay-based derivative-free optimization via global surrogates. II: Convex constraints
• A method for stochastic constrained optimization using derivative-free surrogate pattern search and collocation
• A branch and bound method for stochastic global optimization
• Lipschitzian optimization without the Lipschitz constant
• A progressive barrier derivative-free trust-region algorithm for constrained optimization
• Mesh-based Nelder-Mead algorithm for inequality constrained optimization
• Implementation of Cartesian grids to accelerate Delaunay-based derivative-free optimization
• Bounding averages rigorously using semidefinite programming: mean moments of the Lorenz system
• Efficient solution of quadratically constrained quadratic subproblems within the mesh adaptive direct search algorithm
• Average-cost control of stochastic manufacturing systems.
• Optimal aeroacoustic shape design using the surrogate management framework
• DNS-based predictive control of turbulence: an optimal benchmark for feedback algorithms
• An Introduction to Polynomial and Semi-Algebraic Optimization
• Suppression of vortex-shedding noise via derivative-free shape optimization
• Introduction to Derivative-Free Optimization
• Derivative-Free and Blackbox Optimization
• Global Convergence of General Derivative-Free Trust-Region Algorithms to First- and Second-Order Critical Points
• Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting

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