A modified reduced gradient method for a class of nondifferentiable problems

DOI10.1007/BF01581637zbMath0454.90058OpenAlexW2010003095MaRDI QIDQ3902833

Yves Smeers, Willy Gochet

Publication date: 1980

Published in: Mathematical Programming (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf01581637

zbMATH Keywords

dual problemconvergencenondifferentiable optimizationprimal problemfaithfully convex functionsmodified reduced gradient method

Mathematics Subject Classification ID

Convex programming (90C25)

Related Items (5)

Reversed geometric programming: A branch-and-bound method involving linear subproblems ⋮ A reduced gradient method for quadratic programs with quadratic constraints and \(l_ p-\)constrained \(l_ p-\)approximation problems ⋮ Economic dispatch of thermal power systems using geometric programming ⋮ Flexible contracting. Theory and case examples ⋮ Reduced subgradient bundle method for linearly constrained non-smooth non-convex problems

Cites Work

• A modified reduced gradient method for dual posynomial programming
• Geometric programming: Duality in quadratic programming an \(l_{p}\)- approximation III (Degenerate programs)
• The Convex Simplex Method
• Geometric Programming: Duality in Quadratic Programming and $l_p $-Approximation II (Canonical Programs)
• Convex Analysis
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