Multidimensional global optimization using numerical estimates of objective function derivatives

DOI10.1080/10556788.2019.1630624zbMath1493.90142OpenAlexW2960576163MaRDI QIDQ5865327

Alexey Goryachih, Victor P. Gergel

Publication date: 13 June 2022

Published in: Optimization Methods and Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10556788.2019.1630624

zbMATH Keywords

numerical experimentsLipschitz conditiondimensionality reductionglobal search algorithmsmultiextremal optimizationnumerical estimations of derivative values

Mathematics Subject Classification ID

Nonconvex programming, global optimization (90C26)

Related Items (1)

Multidimensional Global Search Using Numerical Estimations of Minimized Function Derivatives and Adaptive Nested Optimization Scheme

Uses Software

• LGO
• Algorithm 829
• BRENT

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Advances in stochastic and deterministic global optimization
• Adaptive nested optimization scheme for multidimensional global search
• A deterministic global optimization using smooth diagonal auxiliary functions
• The cubic algorithm
• Global optimization of univariate Lipschitz functions. II: New algorithms and computational comparison
• Global one-dimensional optimization using smooth auxiliary functions
• Accelerations for a variety of global optimization methods
• Bayesian algorithms for one-dimensional global optimization
• A global optimization algorithm for multivariate functions with Lipschitzian first derivatives
• Global optimization in one-dimensional case using analytically defined derivatives of objective function
• On a method for computing the values of derivatives in the minimization of multi-extremal functions.
• Global optimization with non-convex constraints. Sequential and parallel algorithms
• A deterministic algorithm for global optimization
• Global optimization in action. Continuous and Lipschitz optimization: algorithms, implementations and applications
• State of the art in global optimization: computational methods and applications. Papers of the conference, Princeton, NJ, USA, April 28--30, 1995
• Operational zones for comparing metaheuristic and deterministic one-dimensional global optimization algorithms
• One-dimensional nested maximin designs
• Convergence conditions and numerical comparison of global optimization methods based on dimensionality reduction schemes
• Stochastic global optimization.
• Introduction to Global Optimization Exploiting Space-Filling Curves
• Simplicial Global Optimization
• A Class of Smooth Modification of Space-Filling Curves for Global Optimization Problems
• Evaluating Derivatives
• Minimization of a multi-extremum function with a discontinuity
• Nested Partitions Method for Global Optimization
• An algorithm for finding the absolute extremum of a function
• Acceleration of Univariate Global Optimization Algorithms Working with Lipschitz Functions and Lipschitz First Derivatives
• Algorithm 829
• A Sequential Method Seeking the Global Maximum of a Function

This page was built for publication: Multidimensional global optimization using numerical estimates of objective function derivatives