Characterizations of \(\varepsilon\)-duality gap statements for composed optimization problems

DOI10.1016/j.na.2013.07.004zbMath1308.49024OpenAlexW2085218413MaRDI QIDQ2254297

Sorin-Mihai Grad, Horaţiu-Vasile Boncea

Publication date: 4 February 2015

Published in: Nonlinear Analysis. Theory, Methods \& Applications. Series A: Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.na.2013.07.004

zbMATH Keywords

optimization problemsconjugate functionsconstraint qualificationsFenchel-Lagrange dual\(\varepsilon\)-subdifferentials\(\varepsilon\)-duality gap

Mathematics Subject Classification ID

Convex programming (90C25) Optimality conditions and duality in mathematical programming (90C46) Nonsmooth analysis (49J52) Semi-infinite programming (90C34) Duality theory (optimization) (49N15)

Related Items (2)

Stable and total Fenchel duality for composed convex optimization problems ⋮ On epsilon-stability in optimization

Cites Work

• New regularity conditions for strong and total Fenchel-Lagrange duality in infinite dimensional spaces
• \(\varepsilon\)-optimality conditions for composed convex optimization problems
• Conjugate duality in convex optimization
• A note on subdifferentials of convex composite functionals
• On \(\varepsilon\)-approximate solutions for convex semidefinite optimization problems
• Characterizations of \(\varepsilon\)-duality gap statements for constrained optimization problems
• New constraint qualification and conjugate duality for composed convex optimization problems
• On strong and total Lagrange duality for convex optimization problems
• Farkas-type results for inequality systems with composed convex functions via conjugate duality
• Duality in Vector Optimization
• A new constraint qualification for the formula of the subdifferential of composed convex functions in infinite dimensional spaces
• Lower semicontinuous type regularity conditions for subdifferential calculus
• Generalized Moreau–Rockafellar results for composed convex functions
• Approximations in Dynamic Zero-Sum Games II
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