A hybrid method fur linearly constrained optimisation problems

DOI10.1080/02331938608843136zbMath0599.90101OpenAlexW2037937851MaRDI QIDQ3735487

Klaus Schönefeld

Publication date: 1986

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331938608843136

zbMATH Keywords

convergence analysislinear constraintsorder of convergencepenalty methodhybrid methodnonlinear objective functionWilson methodcomputation of Kuhn-Tucker- pointsRobinson's-method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Numerical methods based on necessary conditions (49M05) Numerical methods based on nonlinear programming (49M37) Mathematical programming (90C99)

Related Items (2)

On a class fo hybrid methods for smooth constrained optimization ⋮ On the globalization of Wilson-type optimization methods by means of generalized reduced gradient methods

Cites Work

• A globally and quadratically convergent algorithm for general nonlinear programming problems
• On the global and superlinear convergence of a discretized version of Wilson's method
• A feasible conjugate direction method to solve linearly constrained minimization problems
• A Method of Conjugate Directions for Linearly Constrained Nonlinear Programming Problems
• Extension of Davidon’s Variable Metric Method to Maximization Under Linear Inequality and Equality Constraints
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