An unconstrained optimization technique for large-scale linearly constrained convex minimization problems

DOI10.1007/BF02252984zbMath0820.90099OpenAlexW212237665MaRDI QIDQ1337633

Christian Kanzow

Publication date: 14 September 1995

Published in: Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02252984

zbMATH Keywords

large-scale minimizationdifferentiable unconstrained optimizationsmooth convex function

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Nonlinear programming (90C30)

Related Items

Solution of monotone complementarity problems with locally Lipschitzian functions, PARALLEL MULTISPLITTINGS FOR CONSTRAINED OPTIMIZATION, A descent method for a reformulation of the second-order cone complementarity problem, New constrained optimization reformulation of complementarity problems, On the resolution of monotone complementarity problems, On the convergence of asynchronous parallel algorithm for large-scale linearly constrained minimization problem, Limited memory quasi-Newton method for large-scale linearly equality-constrained minimization, A new technique for inconsistent QP problems in the SQP method, An unconstrained smooth minimization reformulation of the second-order cone complementarity problem, A neural network for the linear complementarity problem

Uses Software

• L-BFGS
• tn

Cites Work

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