Regularity and strong sufficient optimality conditions in differentiable optimization problems

DOI10.1080/01630569308816508zbMath0818.90132OpenAlexW2024828886MaRDI QIDQ4293285

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Publication date: 4 July 1994

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01630569308816508

zbMATH Keywords

perturbed optimizationparametrized optimizationmetric regularity of multivalued functionspartial tangent conepseudo-Lipschitz multivalued functionsstrong sufficient optimality conditionstangential approximations of the feasible set

Mathematics Subject Classification ID

Nonsmooth analysis (49J52) Numerical methods based on nonlinear programming (49M37) Programming in abstract spaces (90C48)

Related Items (11)

First- and second-order necessary optimality conditions for optimal control problems governed by stationary Navier-Stokes equations with pure state constraints ⋮ Metric regularity and second-order necessary optimality conditions for minimization problems under inclusion constraints ⋮ Qualification conditions for multivalued functions in Banach spaces with applications to nonsmooth vector optimization problems ⋮ Metric regularity and subdifferential calculus in Banach spaces ⋮ Qualification conditions for calculus rules of coderivatives of multivalued mappings ⋮ Metric regularity for strongly compactly Lipschitzian mappings ⋮ A chain rule for parabolic second-order epiderivatives ⋮ Second-order optimality conditions and solution stability to optimal control problems governed by stationary Navier-Stokes equations ⋮ Verifiable Conditions for Openness and Regularity of Multivalued Mappings in Banach Spaces ⋮ \(L^\infty\)-stability of a parametric optimal control problem governed by semilinear elliptic equations ⋮ Second-order necessary optimality conditions for a class of optimal control problems governed by partial differential equations with pure state constraints

Cites Work

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• DUALITY OF CONVEX FUNCTIONS AND EXTREMUM PROBLEMS
• Set-valued analysis

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