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Preface. 1. General Optimality. 2. Optimization in Metric Spaces. 3. Multifunctions and Marginal Functions in Metric Spaces. 4. Well-Posedness and Weak Well-Posedness in Banach Spaces. 5. Duality in Banach and Hilbert Spaces. Regularization. 6. Necessary Conditions for Optimality and Local Optimality in Normed Spaces. 7. Polynomials. Necessary and Sufficient Conditions of Optimality of Higher Order. 8. Nondifferentiable Optimization. 9. Numerical Aspects. 10. Vector Optimization. Bibliography. Subject Index. Author Index. List of Symbols.
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Add Foundations of Mathematical Optimization: Convex Analysis Without Linearity, Many books on optimization consider only finite dimensional spaces. This volume is unique in its emphasis: the first three chapters develop optimization in spaces without linear structure, and the analog of convex analysis is constructed for this case. Ma, Foundations of Mathematical Optimization: Convex Analysis Without Linearity to the inventory that you are selling on WonderClubX
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Add Foundations of Mathematical Optimization: Convex Analysis Without Linearity, Many books on optimization consider only finite dimensional spaces. This volume is unique in its emphasis: the first three chapters develop optimization in spaces without linear structure, and the analog of convex analysis is constructed for this case. Ma, Foundations of Mathematical Optimization: Convex Analysis Without Linearity to your collection on WonderClub |