Constrained, Global Optimization of Unknown Functions with Lipschitz Continuous Gradients

DOI10.1137/20M1380879zbMath1494.90090arXiv2011.08997OpenAlexW4281614527MaRDI QIDQ5081778

Ufuk Topcu, Arie Israel, A. P. Vinod

Publication date: 17 June 2022

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2011.08997

zbMATH Keywords

global optimizationnonconvex optimizationconstrainedcovering methodsLipschitz continuous gradients

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Approximation methods and heuristics in mathematical programming (90C59)

Uses Software

• Gurobi
• SciPy
• OpenAI Gym
• Spearmint

Cites Work

• Lectures on convex optimization
• Convergence and restart in branch-and-bound algorithms for global optimization. Application to concave minimization and d.c. optimization problems
• Lipschitzian optimization without the Lipschitz constant
• A deterministic algorithm for global optimization
• DC programming: overview.
• Cutting angle method – a tool for constrained global optimization
• A Deterministic Algorithm for Global Optimization
• Data-Driven Science and Engineering
• An algorithm for finding the absolute extremum of a function
• Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting
• A Sequential Method Seeking the Global Maximum of a Function
• Introduction to global optimization.
• On covering method for d.c. optimization.
• Abstract convexity and global optimization
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