Some numerical experience with a globally convergent algorithm for nonlinearly constrained optimization

DOI10.1007/BF00934840zbMath0418.65028OpenAlexW2052204734MaRDI QIDQ1131824

Roger Fletcher, Ian D. Coope

Publication date: 1980

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

Full work available at URL: https://doi.org/10.1007/bf00934840

zbMATH Keywords

global convergencequadratic programmingnonlinear programmingnumerical experiencenonlinearly constrained minimization problems

Mathematics Subject Classification ID

Nonlinear programming (90C30) Numerical optimization and variational techniques (65K10) Quadratic programming (90C20)

Related Items (3)

Decomposition Methods Based on Augmented Lagrangians: A Survey ⋮ Penalty function methods and a duality gap for invex optimization problems ⋮ Global convergence of QPFTH method for large-scale nonlinear sparse constrained optimization

Cites Work

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• An Ideal Penalty Function for Constrained Optimization
• Combined Primal–Dual and Penalty Methods for Convex Programming
• A set of geometric programming test problems and their solutions
• Dual Variable Metric Algorithms for Constrained Optimization
• Quadratic termination properties of Davidon's new variable metric algorithm
• Some examples of cycling in variable metric methods for constrained minimization
• On the Local and Superlinear Convergence of Quasi-Newton Methods

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