A trust region method for minimization of nonsmooth functions with linear constraints

DOI10.1007/BF02614392zbMath0871.90088MaRDI QIDQ1356054

José Mario Martínez, Antonio Carlos Moretti

Publication date: 9 October 1997

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

zbMATH Keywords

global convergenceparameter estimationlinear constraintstrust region algorithmminimization of nonsmooth functions

Mathematics Subject Classification ID

Nonlinear programming (90C30) Nonsmooth analysis (49J52)

Related Items

A trust region method for solving linearly constrained locally Lipschitz optimization problems, A new filter method for solving nonlinear complementarity problems, A Proximal Quasi-Newton Trust-Region Method for Nonsmooth Regularized Optimization, The approximation algorithm for solving a sort of non-smooth programming, A proximal trust-region method for nonsmooth optimization with inexact function and gradient evaluations, Smoothing trust region methods for nonlinear complementarity problems with \(P_0\)-functions, The chain rule for VU-decompositions of nonsmooth functions, Smoothing methods for nonsmooth, nonconvex minimization

Uses Software

• OSL

Cites Work

• Unnamed Item
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• Conditions for convergence of trust region algorithms for nonsmooth optimization
• Global Convergence of a Class of Trust Region Algorithms for Optimization with Simple Bounds
• Minimization of Locally Lipschitzian Functions
• Monotone Operators and the Proximal Point Algorithm
• On the Resolution of Linearly Constrained Convex Minimization Problems
• Global Convergence of a Class of Trust Region Algorithms for Optimization Using Inexact Projections on Convex Constraints
• Iteration Functions in Some Nonsmooth Optimization Algorithms
• Convex Analysis