9780792374954 - generalized concavity in fuzzy optimization and decision analysis: 41 di ramík, jaroslav; vlach, milan (15 risultati)
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Editore: Springer, 2001
Serie: Libro 33 di 323 - International Series in Operations Research & Management Science
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Condizione: New. pp. 316.
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Editore: Kluwer Academic Publishers, 2001
Serie: Libro 33 di 323 - International Series in Operations Research & Management Science
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Condizione: New. Focuses on the types of generalized convex sets and generalized concave functions. This book investigates decision-making and optimization problems under uncertainty. It outlines and discusses a combination of ideas and results from the field of generalized concavity and fuzzy optimization. Series: International… Series in Operations Research & Management Science. Num Pages: 296 pages, biography. BIC Classification: PBCD; PBW; UM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 19. Weight in Grams: 620. . 2001. Hardback. . . . .
Lingua: Inglese
Editore: Kluwer Academic Publishers, 2001
Serie: Libro 33 di 323 - International Series in Operations Research & Management Science
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Condizione: New. Focuses on the types of generalized convex sets and generalized concave functions. This book investigates decision-making and optimization problems under uncertainty. It outlines and discusses a combination of ideas and results from the field of generalized concavity and fuzzy optimization. Series: International… Series in Operations Research & Management Science. Num Pages: 296 pages, biography. BIC Classification: PBCD; PBW; UM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 19. Weight in Grams: 620. . 2001. Hardback. . . . . Books ship from the US and Ireland.
Lingua: Inglese
Editore: Springer, Springer, 2001
Serie: Libro 33 di 323 - International Series in Operations Research & Management Science
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Convexity of sets in linear spaces, and concavity and convexity of functions, lie at the root of beautiful theoretical results that are at the same time extremely useful in the analysis and solution of optimization problems, including problems of either…single objective or multiple objectives. Not all of these results rely necessarily on convexity and concavity; some of the results can guarantee that each local optimum is also a global optimum, giving these methods broader application to a wider class of problems. Hence, the focus of the first part of the book is concerned with several types of generalized convex sets and generalized concave functions. In addition to their applicability to nonconvex optimization, these convex sets and generalized concave functions are used in the book's second part, where decision-making and optimization problems under uncertainty are investigated. Uncertainty in the problem data often cannot be avoided when dealing with practical problems. Errors occur in real-world data for a host of reasons. However, over the last thirty years, the fuzzy set approach has proved to be useful in these situations. It is this approach to optimization under uncertainty that is extensively used and studied in the second part of this book. Typically, the membership functions of fuzzy sets involved in such problems are neither concave nor convex. They are, however, often quasiconcave or concave in some generalized sense. This opens possibilities for application of results on generalized concavity to fuzzy optimization. Despite this obvious relation, applying the interface of these two areas has been limited to date. It is hoped that the combination of ideas and results from the field of generalized concavity on the one hand and fuzzy optimization on the other hand outlined and discussed in Generalized Concavity in Fuzzy Optimization and Decision Analysis will be of interest to both communities. Our aimis to broaden the classes of problems that the combination of these two areas can satisfactorily address and solve.
Lingua: Inglese
Editore: Springer, 2001
Serie: Libro 33 di 323 - International Series in Operations Research & Management Science
- Rilegato
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Condizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Springer, 2001
Serie: Libro 33 di 323 - International Series in Operations Research & Management Science
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Hardcover. Condizione: Like New. Like New. book.
Lingua: Inglese
Editore: Springer, 2001
Serie: Libro 33 di 323 - International Series in Operations Research & Management Science
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Serie: Libro 33 di 323 - International Series in Operations Research & Management Science
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Convexity of sets in linear spaces, and concavity and convexity of functions, lie at the root of beautiful theoretical results that are at the same time extremely useful in the analysis and solution of optimization problems, including pro…blems of either single objective or multiple objectives. Not all of these results rely necessarily on convexity and concavity; some of the results can guarantee that each local optimum is also a global optimum, giving these methods broader application to a wider class of problems. Hence, the focus of the first part of the book is concerned with several types of generalized convex sets and generalized concave functions. In addition to their applicability to nonconvex optimization, these convex sets and generalized concave functions are used in the book's second part, where decision-making and optimization problems under uncertainty are investigated. Uncertainty in the problem data often cannot be avoided when dealing with practical problems. Errors occur in real-world data for a host of reasons. However, over the last thirty years, the fuzzy set approach has proved to be useful in these situations. It is this approach to optimization under uncertainty that is extensively used and studied in the second part of this book. Typically, the membership functions of fuzzy sets involved in such problems are neither concave nor convex. They are, however, often quasiconcave or concave in some generalized sense. This opens possibilities for application of results on generalized concavity to fuzzy optimization. Despite this obvious relation, applying the interface of these two areas has been limited to date. It is hoped that the combination of ideas and results from the field of generalized concavity on the one hand and fuzzy optimization on the other hand outlined and discussed in Generalized Concavity in Fuzzy Optimization and Decision Analysis will be of interest to both communities. Our aimis to broaden the classes of problems that the combination of these two areas can satisfactorily address and solve. 316 pp. Englisch.
Lingua: Inglese
Editore: Springer US, 2001
Serie: Libro 33 di 323 - International Series in Operations Research & Management Science
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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Convexity of sets in linear spaces, and concavity and convexity of functions, lie at the root of beautiful theoretical results that are at the same time extremely useful in the analysis and solution of opti…mization problems, including problems of either .
Lingua: Inglese
Editore: Springer, 2001
Serie: Libro 33 di 323 - International Series in Operations Research & Management Science
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Condizione: New. Print on Demand pp. 316 Illus.
Lingua: Inglese
Editore: Springer, 2001
Serie: Libro 33 di 323 - International Series in Operations Research & Management Science
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. 316.
Lingua: Inglese
Editore: Springer, Springer Sep 2001, 2001
Serie: Libro 33 di 323 - International Series in Operations Research & Management Science
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Convexity of sets in linear spaces, and concavity and convexity of functions, lie at the root of beautiful theoretical results that are at the same time extremely useful in the analysis and solution of optimization problems, including problem…s of either single objective or multiple objectives. Not all of these results rely necessarily on convexity and concavity; some of the results can guarantee that each local optimum is also a global optimum, giving these methods broader application to a wider class of problems. Hence, the focus of the first part of the book is concerned with several types of generalized convex sets and generalized concave functions. In addition to their applicability to nonconvex optimization, these convex sets and generalized concave functions are used in the book's second part, where decision-making and optimization problems under uncertainty are investigated.Uncertainty in the problem data often cannot be avoided when dealing with practical problems. Errors occur in real-world data for a host of reasons. However, over the last thirty years, the fuzzy set approach has proved to be useful in these situations. It is this approach to optimization under uncertainty that is extensively used and studied in the second part of this book. Typically, the membership functions of fuzzy sets involved in such problems are neither concave nor convex. They are, however, often quasiconcave or concave in some generalized sense. This opens possibilities for application of results on generalized concavity to fuzzy optimization. Despite this obvious relation, applying the interface of these two areas has been limited to date. It is hoped that the combination of ideas and results from the field of generalized concavity on the one hand and fuzzy optimization on the other hand outlined and discussed in Generalized Concavity in Fuzzy Optimization and Decision Analysis will be of interest to both communities. Our aimis to broaden the classes of problems that the combination of these two areas can satisfactorily address and solve.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 316 pp. Englisch.
