A smoothing trust-region Newton-CG method for minimax problem

DOI10.1016/j.amc.2007.10.070zbMath1146.65053OpenAlexW2024370928MaRDI QIDQ928081

Liu Hongwei, Ye Feng, Zhou Shuisheng, Liu Sanyang

Publication date: 11 June 2008

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2007.10.070

zbMATH Keywords

unconstrained optimizationsmoothing techniquetrust-region methodsuccessive quadratic programming (SQP)finite minimax problemsSQP algorithmNewton conjugate gradient (CG) methodNewton-CG algorithm

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Minimax problems in mathematical programming (90C47) Interior-point methods (90C51)

Related Items (19)

A globally convergent QP-free algorithm for inequality constrained minimax optimization ⋮ The optimization technique for solving a class of non-differentiable programming based on neural network method ⋮ Substitution secant/finite difference method to large sparse minimax problems ⋮ Rate of convergence analysis of discretization and smoothing algorithms for semiinfinite minimax problems ⋮ An active set strategy to address the ill-conditioning of smoothing methods for solving finite linear minimax problems ⋮ A nonlinear augmented Lagrangian for constrained minimax problems ⋮ An \(\varepsilon\)-generalized gradient projection method for nonlinear minimax problems ⋮ Uniform approximation of min/max functions by smooth splines ⋮ An adaptive nonmonotone trust-region method with curvilinear search for minimax problem ⋮ A new objective penalty function approach for solving constrained minimax problems ⋮ A generalized gradient projection method based on a new working set for minimax optimization problems with inequality constraints ⋮ An active-set algorithm and a trust-region approach in constrained minimax problem ⋮ On smooth relaxations of obstacle sets ⋮ On solving large-scale finite minimax problems using exponential smoothing ⋮ A smoothing self-adaptive Levenberg-Marquardt algorithm for solving system of nonlinear inequalities ⋮ New exact penalty function for solving constrained finite min-max problems ⋮ Hyperbolic smoothing function method for minimax problems ⋮ An active set smoothing method for solving unconstrained minimax problems ⋮ Improved filter-SQP algorithm with active set for constrained minimax problems

Uses Software

• Matlab

Cites Work

• Unnamed Item
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• New minimax algorithm
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• An efficient algorithm for the smallest enclosing ball problem in high dimensions
• The Conjugate Gradient Method and Trust Regions in Large Scale Optimization
• Adaptive control of ARMA plants using worst-case design by semi-infinite optimization
• Variable metric methods for minimizing a class of nondifferentiable functions
• A smoothing-out technique for min—max optimization
• An Efficient Method to Solve the Minimax Problem Directly
• Numerical Optimization
• Linear-Quadratic Programming and Optimal Control
• An Algorithm for Minimax Approximation in the Nonlinear Case

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