A truncated aggregate smoothing Newton method for minimax problems
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Publication:979271
DOI10.1016/j.amc.2009.11.034zbMath1194.65083OpenAlexW2016115300MaRDI QIDQ979271
Publication date: 25 June 2010
Published in: Applied Mathematics and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.amc.2009.11.034
algorithmglobal convergencenumerical resultsminimax problemslocally quadratic convergencestabilized Newton methodtruncated aggregate function
Numerical mathematical programming methods (65K05) Minimax problems in mathematical programming (90C47) Methods of quasi-Newton type (90C53)
Related Items (14)
An efficient inexact Newton-CG algorithm for the smallest enclosing ball problem of large dimensions ⋮ Global convergence analysis of the aggregate constraint homotopy method for nonlinear programming problems with both inequality and equality constraints ⋮ An active set strategy to address the ill-conditioning of smoothing methods for solving finite linear minimax problems ⋮ Unnamed Item ⋮ Flattened aggregate function method for nonlinear programming with many complicated constraints ⋮ The optimality conditions for generalized minimax programming ⋮ A homotopy method based on penalty function for nonlinear semidefinite programming ⋮ A generalized gradient projection method based on a new working set for minimax optimization problems with inequality constraints ⋮ A spline smoothing Newton method for finite minimax problems ⋮ Zero duality gap in surrogate constraint optimization: a concise review of models ⋮ Truncated aggregate homotopy method for nonconvex nonlinear programming ⋮ Hyperbolic smoothing function method for minimax problems ⋮ An active set smoothing method for solving unconstrained minimax problems ⋮ An aggregate homotopy method for solving unconstrained minimax problems
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