A recursive quadratic programming algorithm that uses differentiable exact penalty functions

DOI10.1007/BF01580880zbMath0598.90079OpenAlexW1994707765MaRDI QIDQ3734178

M. J. D. Powell, Ya-Xiang Yuan

Publication date: 1986

Published in: Mathematical Programming (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01580880

zbMATH Keywords

line searchGlobal convergencelocal superlinear convergencerecursive quadratic programmingdifferentiable exact penalty functionapproximations to the derivatives of Lagrange multipliersequality constrained nonlinear minimization

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Quadratic programming (90C20) Numerical methods based on nonlinear programming (49M37)

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Uses Software

• NPSOL

Cites Work

• The nonlinear programming method of Wilson, Han, and Powell with an augmented Lagrangian type line search function. I. Convergence analysis
• A globally convergent method for nonlinear programming
• On the convergence of a sequential quadratic programming method with an augmented lagrangian line search function
• Recursive quadratic programming methods based on the augmented lagrangian
• The watchdog technique for forcing convergence in algorithms for constrained optimization
• On the Local Convergence of Quasi-Newton Methods for Constrained Optimization
• Superlinearly convergent variable metric algorithms for general nonlinear programming problems
• On the Convergence of Some Constrained Minimization Algorithms Based on Recursive Quadratic Programming
• An exact penalty function for nonlinear programming with inequalities
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