9780691143682 - robust optimization: 28 (princeton series in applied mathematics) de ben-tal, aharon; arkadi nemirovski; el ghaoui, laurent (20 resultados)
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Serie: Princeton Series in Applied Mathematics, Libro 7 de 33. Libro 7 de 33 - Princeton Series in Applied Mathematics
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Condición: New. 2009. Hardcover. Features simple treatment of uncertain linear programming. This book also presents an analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. Series: Princeton Series in Applied Mathematics. Num Pages…: 576 pages, 36 line illus. 41 tables. BIC Classification: PBUH. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 261 x 187 x 36. Weight in Grams: 1312. . . . . .
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Hardback. Condición: New. Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robus…t optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach.It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.
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Hardback. Condición: New. Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robus…t optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach.It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.
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Hardcover. Condición: new. Hardcover. Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal develop…ers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach.It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject. Features simple treatment of uncertain linear programming. This book also presents an analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Condición: New. 2009. Hardcover. Features simple treatment of uncertain linear programming. This book also presents an analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. Series: Princeton Series in Applied Mathematics. Num Pages…: 576 pages, 36 line illus. 41 tables. BIC Classification: PBUH. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 261 x 187 x 36. Weight in Grams: 1312. . . . . . Books ship from the US and Ireland.
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Hardback. Condición: New. Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robus…t optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach.It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.
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Hardback. Condición: New. Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robus…t optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach.It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.
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Hardcover. Condición: Brand New. 576 pages. 9.90x7.30x1.50 inches. In Stock.
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Hardcover. Condición: new. Hardcover. Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal develop…ers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach.It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject. Features simple treatment of uncertain linear programming. This book also presents an analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Robust Optimization
Aharon Bental|Laurent El Ghaoui|Arkadi Nemirovski|Laurent El Ghaoui|Arkadi Nemirovski
Idioma: Inglés
Editorial: Princeton University Press 2009
Serie: Princeton Series in Applied Mathematics, Libro 7 de 33. Libro 7 de 33 - Princeton Series in Applied Mathematics
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Features simple treatment of uncertain linear programming. This book also presents an analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (pro…babilistic) approach.Über d.
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Hardcover. Condición: Brand New. 576 pages. 9.90x7.30x1.50 inches. In Stock. This item is printed on demand.
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Buch. Condición: Neu. Robust Optimization | Aharon Ben-Tal (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2009 | Princeton University Press | EAN 9780691143682 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
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Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerf…ul methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject.Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution.The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations.An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.
