9781493922819 - bonus algorithm for large scale stochastic nonlinear programming problems di diwekar, urmila; david, amy (13 risultati)
Lingua: Inglese
Editore: Springer, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Lingua: Inglese
Editore: Springer-Verlag New York Inc., New York, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Paperback. Condizione: new. Paperback. This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. A generalized… method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these methods assume that there are a small number of scenarios to be evaluated for calculation of the probabilistic objective function and constraints. This book begins to tackle these issues by describing a generalized method for stochastic nonlinear programming problems. This title is best suited for practitioners, researchers and students in engineering, operations research, and management science who desire a complete understanding of the BONUS algorithm and its applications to the real world. This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Springer, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New.
Lingua: Inglese
Editore: Springer Verlag, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 146 pages. 9.00x6.00x0.50 inches. In Stock.
Lingua: Inglese
Editore: Springer New York, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Da: moluna, Greven, Germaniamoluna
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Condizione: New.
Altre immaginiLingua: Inglese
Editore: Springer, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. BONUS Algorithm for Large Scale Stochastic Nonlinear Programming Problems | Urmila Diwekar (u. a.) | Taschenbuch | xviii | Englisch | 2015 | Springer | EAN 9781493922819 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[d…ot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer, Springer, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacit…y expansion of energy systems. A generalized method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these methods assume that there are a small number of scenarios to be evaluated for calculation of the probabilistic objective function and constraints. This book begins to tackle these issues by describing a generalized method for stochastic nonlinear programming problems. This title is best suited for practitioners, researchers and students in engineering, operations research, and management science who desire a complete understanding of the BONUS algorithm and its applications to the real world.
Lingua: Inglese
Editore: Springer-Verlag New York Inc., New York, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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Paperback. Condizione: new. Paperback. This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. A generalized… method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these methods assume that there are a small number of scenarios to be evaluated for calculation of the probabilistic objective function and constraints. This book begins to tackle these issues by describing a generalized method for stochastic nonlinear programming problems. This title is best suited for practitioners, researchers and students in engineering, operations research, and management science who desire a complete understanding of the BONUS algorithm and its applications to the real world. This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Lingua: Inglese
Editore: Springer, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer New York Mrz 2015, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power syst…ems, and capacity expansion of energy systems. A generalized method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these methods assume that there are a small number of scenarios to be evaluated for calculation of the probabilistic objective function and constraints. This book begins to tackle these issues by describing a generalized method for stochastic nonlinear programming problems. This title is best suited for practitioners, researchers and students in engineering, operations research, and management science who desire a complete understanding of the BONUS algorithm and its applications to the real world. 164 pp. Englisch.
Lingua: Inglese
Editore: Springer, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand.
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Editore: Springer, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: Springer, Springer Mär 2015, 2015
Serie: SpringerBriefs in Optimization, Libro 25 di 43. Libro 25 di 43 - SpringerBriefs in Optimization
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems,… and capacity expansion of energy systems. A generalized method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these methods assume that there are a small number of scenarios to be evaluated for calculation of the probabilistic objective function and constraints. This book begins to tackle these issues by describing a generalized method for stochastic nonlinear programming problems. This title is best suited for practitioners, researchers and students in engineering, operations research, and management science who desire a complete understanding of the BONUS algorithm and its applications to the real world.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 164 pp. Englisch.
