On a Newton-like method for constrained nonlinear minimization via slack variables

DOI10.1007/BF00933828zbMath0452.90067OpenAlexW2089849329MaRDI QIDQ1148811

Emilio Spedicato

Publication date: 1982

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

Full work available at URL: https://doi.org/10.1007/bf00933828

zbMATH Keywords

global convergencelocal convergenceconstrained minimizationslack variablesKuhn-Tucker conditionsquasi-Newton diagonalized approach

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Rate of convergence, degree of approximation (41A25)

Related Items

The use of squared slack variables in nonlinear second-order cone programming, A special newton-type optimization method, Newton-type methods for nonlinearly constrained programming problems-algorithms and theory

Cites Work

• Diagonalized multiplier methods and quasi-Newton methods for constrained optimization
• The prerestorative step in the sequential gradient-restoration algorithm for mathematical programming problems with inequality constraints
• A stable approach to Newton's method for general mathematical programming problems in R\(^n\)
• A New Class of Augmented Lagrangians in Nonlinear Programming
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