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Characterizations of optimality without constraint qualification for the abstract convex program

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Outgoing claims: the papers this work cites, builds on, or argues with.

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Calculating the cone of directions of constancy
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Characterization of optimality in convex programming without a constraint qualification
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A simplified test for optimality
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Regularity and stability for the mathematical programming problem in Banach spaces
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Geometry of optimality conditions and constraint qualifications: The convex case
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Geometry of optimality conditions and constraint qualifications
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A Course on Optimization and Best Approximation
inferredcites →https://doi.org/10.1007/bfb0120983openalex-snapshot
Characterizations of optimality without constraint qualification for the abstract convex program
inferredcites →https://doi.org/10.1016/b978-0-12-597050-1.50014-2openalex-snapshot
Some Convex Programs Whose Duals Are Linearly Constrained
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Optimization by Vector Space Methods
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Nonlinear programming without differentiability in banach spaces: necessary and sufficient constraint qualification
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Characterizations of optimality in convex programming: the nondifferentiable case
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Characterizations of optimality in convex programming: the nondifferentiable case
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Complete characterization of optimality for convex programming in banach spaces†
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A Necessary and Sufficient Qualification for Constrained Optimization
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Generalized Kuhn–Tucker Conditions for Mathematical Programming Problems in a Banach Space
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Proper Efficient Points for Maximizations with Respect to Cones
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Optimization: A Theory of Necessary Conditions
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Nonlinear Programming
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Necessary Conditions for an Extremum

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Bibliographical Description
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Bibliographical Description
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Bibliographical Description
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Điều kiện cần và đủ theo dãy cho nghiệm của bài toán tối ưu với ràng buộc nhúng
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Sequential Optimality Conditions in Convex Programming via Perturbation Approach
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