A limiting Lagrangian for infinitely-constrained convex optimization in \(\mathbb{R}^n\)

DOI10.1007/BF00935754zbMath0427.49030OpenAlexW2082317817MaRDI QIDQ1136349

Robert G. Jeroslow

Publication date: 1981

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

Full work available at URL: https://doi.org/10.1007/bf00935754

zbMATH Keywords

convex optimizationconstrained optimizationnonlinear programmingLagrangiansKuhn-Tucker theory

Mathematics Subject Classification ID

Convex programming (90C25) Numerical methods involving duality (49M29) Methods of successive quadratic programming type (90C55)

Related Items (9)

Asymptotic dual conditions characterizing optimality for infinite convex programs ⋮ Uniform duality in semi-infinite convex optimization ⋮ The limiting Lagrangian as a consequence of Helly's theorem ⋮ A limiting infisup theorem ⋮ Reduction and Discrete Approximation in Linear Semi-Infinite Programming ⋮ A note on d-stability of convex programs and limiting Lagrangians ⋮ A note on limiting infisup theorems ⋮ Zero duality gaps in infinite-dimensional programming ⋮ Limiting Lagrangians: A primal approach

Cites Work

• A note on infinite systems of linear inequalities in R\(^n\)
• Affine minorants minimizing the sum of convex functions
• Constructing a perfect duality in infinite programming
• Lagrangean functions and affine minorants
• Convex optimization and lagrange multipliers
• An Infinite Linear Program with a Duality Gap
• On Representations of Semi-Infinite Programs which Have No Duality Gaps
• Convex Analysis
• Convex analysis treated by linear programming

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