Globally convergent version of Robinson's algorithm for general nonlinear programming problems without using derivatives

DOI10.1007/BF00934576zbMath0438.90077MaRDI QIDQ1142159

J. Bräuninger

Publication date: 1981

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

zbMATH Keywords

penalty functionslinear constraintspenalty function methodnonlinear constraintsapproximations of derivativesderivative-free minimizationglobally convergent versionlocally convergent algorithmquadratically convergent algorithmRobinson's algorithm

Mathematics Subject Classification ID

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

Related Items (1)

On a class fo hybrid methods for smooth constrained optimization

Cites Work

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• A globally and quadratically convergent algorithm for general nonlinear programming problems
• A quasi-Newton method for minimization under linear constraints without evaluating any derivatives
• An Adaptive Random Search Algorithm for Constrained Minimization
• Penalty function versus non-penalty function methods for constrained nonlinear programming problems
• A quadratically-convergent algorithm for general nonlinear programming problems

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