On superlinear convergence in univariate nonsmooth minimization

DOI10.1007/BF01588792zbMath0719.90073MaRDI QIDQ2640452

Robert Mifflin

Publication date: 1990

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

zbMATH Keywords

nonsmooth optimizationone-sided superlinear convergence resultunivariate locally Lipschitz function

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Computational methods for problems pertaining to operations research and mathematical programming (90-08)

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Cites Work

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• A bracketing technique to ensure desirable convergence in univariate minimization
• Steplength algorithms for minimizing a class of nondifferentiable functions
• A rapidly convergent five-point algorithm for univariate minimization
• Stationarity and superlinear convergence of an algorithm for univariate locally lipschitz constrained minimization
• An efficient algorithm for minimizing a multivariate polyhedral function along a line
• An implementation of an algorithm for univariate minimization and an application to nested optimization
• Global and superlinear convergence of an algorithm for one-dimensional minimization of convex functions