The regularized feasible directions method for nonconvex optimization

DOI10.1016/j.orl.2022.07.005OpenAlexW4288942171MaRDI QIDQ2084025

Amir Beck, Nadav Hallak

Publication date: 17 October 2022

Published in: Operations Research Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.orl.2022.07.005

zbMATH Keywords

convergence analysisnonsmooth optimizationconstrained optimizationnonconvex optimizationfeasible directions

Mathematics Subject Classification ID

Operations research, mathematical programming (90-XX)

Uses Software

• polymake

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Introductory lectures on convex optimization. A basic course.
• Finding second-order stationary points in constrained minimization: a feasible direction approach
• On the properties of positive spanning sets and positive bases
• Computing convex hulls and counting integer points with \texttt{polymake}
• Convergence of an inexact majorization-minimization method for solving a class of composite optimization problems
• A Unified Convergence Analysis of Block Successive Minimization Methods for Nonsmooth Optimization
• Computing Points that Satisfy Second Order Necessary Optimality Conditions for Unconstrained Minimization
• Introduction to Derivative-Free Optimization
• Lectures on Polytopes
• First-Order Methods in Optimization
• On the Convergence to Stationary Points of Deterministic and Randomized Feasible Descent Directions Methods
• Nonlinear Programming
• Theory of Positive Linear Dependence
• Generating all vertices of a polyhedron is hard

This page was built for publication: The regularized feasible directions method for nonconvex optimization