On solving three classes of nonlinear programming problems via simple differentiable penalty functions

DOI10.1007/BF00938528zbMath0616.90061OpenAlexW2076493176MaRDI QIDQ1821693

Yanyan Li

Publication date: 1988

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf00938528

zbMATH Keywords

minimax problemsmooth functionsquadratic penalty functionsnonlinear \(\ell _ 1\)- problemsimple bounds on the variables

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Numerical methods based on nonlinear programming (49M37)

Related Items (3)

A simple algorithm to incorporate transactions costs in quadratic optimization ⋮ Maximizing pseudoconvex transportation problem: A special type ⋮ A new penalty function algorithm for convex quadratic programming

Cites Work

• A globally convergent method for nonlinear programming
• Factorizing symmetric indefinite matrices
• Minimization of functions having Lipschitz continuous first partial derivatives
• On the Accurate Determination of Search Directions for Simple Differentiable Penalty Functions
• Combined LP and Quasi-Newton Methods for Nonlinear $l_1 $ Optimization
• Discrete Chebyshev Approximation with Linear Constraints
• A Projected Lagrangian Algorithm for Nonlinear Minimax Optimization
• A Projected Lagrangian Algorithm for Nonlinear $l_1 $ Optimization
• Some Stable Methods for Calculating Inertia and Solving Symmetric Linear Systems
• An Algorithm for $l_1 $-Norm Minimization with Application to Nonlinear $l_1 $-Approximation
• The Minimax Solution of an Overdetermined System of Non-linear Equations
• Quasi-Newton Methods and their Application to Function Minimisation
• On an algorithm for discrete nonlinear L1 approximation
• Robust Statistics
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