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Foundations of Mathematical Optimization: Convex Analysis without Linearity: 388 (Mathematics and Its Applications) - Hardcover
Inhaltsangabe
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. Many new results have been proved specially for this publication. In the following chapters optimization in infinite topological and normed vector spaces is considered. The novelty consists in using the drop property for weak well-posedness of linear problems in Banach spaces and in a unified approach (by means of the Dolecki approximation) to necessary conditions of optimality. The method of reduction of constraints for sufficient conditions of optimality is presented. The book contains an introduction to non-differentiable and vector optimization.
Audience: This volume will be of interest to mathematicians, engineers, and economists working in mathematical optimization.
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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. Many new results have been proved specially for this publication. In the following chapters optimization in infinite topological and normed vector spaces is considered. The novelty consists in using the drop property for weak well-posedness of linear problems in Banach spaces and in a unified approach (by means of the Dolecki approximation) to necessary conditions of optimality. The method of reduction of constraints for sufficient conditions of optimality is presented. The book contains an introduction to non-differentiable and vector optimization.
Audience: This volume will be of interest to mathematicians, engineers, and economists working in mathematical optimization.
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Foundations of Mathematical Optimization : Convex Analysis without Linearity
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Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 604 | Sprache: Englisch | Produktart: Bücher. Artikel-Nr. 3029038/202
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Foundations of Mathematical Optimization : Convex Analysis without Linearity
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Zustand: Gut. Zustand: Gut | Seiten: 604 | Sprache: Englisch | Produktart: Bücher. Artikel-Nr. 3029038/203
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Foundations of Mathematical Optimization
Verlag:
Springer Netherlands, Springer Netherlands Feb 1997, 1997
ISBN 10: 0792344243
ISBN 13: 9780792344247
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Hardcover
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Buch. Zustand: Neu. Neuware -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. Many new results have been proved specially for this publication. In the following chapters optimization in infinite topological and normed vector spaces is considered. The novelty consists in using the drop property for weak well-posedness of linear problems in Banach spaces and in a unified approach (by means of the Dolecki approximation) to necessary conditions of optimality. The method of reduction of constraints for sufficient conditions of optimality is presented. The book contains an introduction to non-differentiable and vector optimization.Audience: This volume will be of interest to mathematicians, engineers, and economists working in mathematical optimization.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 604 pp. Englisch. Artikel-Nr. 9780792344247
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Foundations of Mathematical Optimization: Convex Analysis without Linearity (Mathematics and Its Applications, 388)
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Foundations of Mathematical Optimization : Convex Analysis without Linearity
Verlag:
Springer Netherlands, Springer Netherlands, 1997
ISBN 10: 0792344243
ISBN 13: 9780792344247
Neu
Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Many new results have been proved specially for this publication. In the following chapters optimization in infinite topological and normed vector spaces is considered. The novelty consists in using the drop property for weak well-posedness of linear problems in Banach spaces and in a unified approach (by means of the Dolecki approximation) to necessary conditions of optimality. The method of reduction of constraints for sufficient conditions of optimality is presented. The book contains an introduction to non-differentiable and vector optimization. Audience: This volume will be of interest to mathematicians, engineers, and economists working in mathematical optimization. Artikel-Nr. 9780792344247
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