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2: Theory and extensions / George B. Dantzig, Mukund N. Thapa
| 2: Theory and extensions / George B. Dantzig, Mukund N. Thapa |
| Autore | Dantzig, George B. |
| Pubbl/distr/stampa | New York, : Springer, 2003 |
| Descrizione fisica | XXV, 448 p. ; 27 cm. |
| Altri autori (Persone) | Thapa, Mukund N. |
| Soggetto topico |
90C05 - Linear programming [MSC 2020]
90C51 - Interior-point methods [MSC 2020] 90C46 - Optimality conditions and duality in mathematical programming [MSC 2020] 90B06 - Transportation, logistics and supply chain management [MSC 2020] 90B10 - Deterministic network models in operations research [MSC 2020] 90C15 - Stochastic programming [MSC 2020] |
| ISBN | 03-87986-13-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-SUN0060529 |
Dantzig, George B.
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| New York, : Springer, 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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2: Theory and extensions / George B. Dantzig, Mukund N. Thapa
| 2: Theory and extensions / George B. Dantzig, Mukund N. Thapa |
| Autore | Dantzig, George B. |
| Pubbl/distr/stampa | New York, : Springer, 2003 |
| Descrizione fisica | XXV, 448 p. ; 27 cm |
| Altri autori (Persone) | Thapa, Mukund N. |
| Soggetto topico |
90C05 - Linear programming [MSC 2020]
90C51 - Interior-point methods [MSC 2020] 90C46 - Optimality conditions and duality in mathematical programming [MSC 2020] 90B06 - Transportation, logistics and supply chain management [MSC 2020] 90B10 - Deterministic network models in operations research [MSC 2020] 90C15 - Stochastic programming [MSC 2020] |
| ISBN | 03-87986-13-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0060529 |
|
Dantzig, George B.
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| New York, : Springer, 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
2: Theory and extensions / George B. Dantzig, Mukund N. Thapa
| 2: Theory and extensions / George B. Dantzig, Mukund N. Thapa |
| Autore | Dantzig, George B. |
| Pubbl/distr/stampa | New York, : Springer, 2003 |
| Descrizione fisica | xxv, 448 p. ; 27 cm |
| Altri autori (Persone) | Thapa, Mukund N. |
| Soggetto topico |
90B06 - Transportation, logistics and supply chain management [MSC 2020]
90B10 - Deterministic network models in operations research [MSC 2020] 90C05 - Linear programming [MSC 2020] 90C15 - Stochastic programming [MSC 2020] 90C46 - Optimality conditions and duality in mathematical programming [MSC 2020] 90C51 - Interior-point methods [MSC 2020] |
| ISBN | 03-87986-13-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00060529 |
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Dantzig, George B.
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| New York, : Springer, 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
An Accelerated Solution Method for Two-Stage Stochastic Models in Disaster Management / Emilia Graß
| An Accelerated Solution Method for Two-Stage Stochastic Models in Disaster Management / Emilia Graß |
| Autore | Graß, Emilia |
| Pubbl/distr/stampa | Wiesbaden, : Springer Spektrum, 2018 |
| Descrizione fisica | xvii, 155 p. : ill. ; 24 cm |
| Soggetto topico |
90C90 - Applications of mathematical programming [MSC 2020]
90C51 - Interior-point methods [MSC 2020] 90C15 - Stochastic programming [MSC 2020] 90B50 - Management decision making, including multiple objectives [MSC 2020] 90-XX - Operations research, mathematical programming [MSC 2020] 90C59 - Approximation methods and heuristics in mathematical programming [MSC 2020] |
| Soggetto non controllato |
Accelerated L-Shaped Method
Case Studies in Disaster Management Disaster management Hurricane Katrina Case Study Hurricane-prone Atlantic Coast Hurricane-prone Gulf Coast Interior-Point Method L-Shaped Method Short-term Disaster Warnings Solution Method Two-Stage Stochastic Models Two-Stage Stochastic Programming |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0124479 |
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Graß, Emilia
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||
| Wiesbaden, : Springer Spektrum, 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
An Accelerated solution method for two-stage stochastic models in disaster management / Emilia Graß
| An Accelerated solution method for two-stage stochastic models in disaster management / Emilia Graß |
| Autore | Graß, Emilia |
| Pubbl/distr/stampa | Wiesbaden, : Springer Spektrum, 2018 |
| Descrizione fisica | 1 testo elettronico (XVII, 155 p. : ill.) |
| Soggetto topico |
90-XX - Operations research, mathematical programming [MSC 2020]
90B50 - Management decision making, including multiple objectives [MSC 2020] 90C15 - Stochastic programming [MSC 2020] 90C51 - Interior-point methods [MSC 2020] 90C59 - Approximation methods and heuristics in mathematical programming [MSC 2020] 90C90 - Applications of mathematical programming [MSC 2020] |
| Soggetto non controllato |
Accelerated L-Shaped Method
Case Studies in Disaster Management Disaster management Hurricane Katrina Case Study Hurricane-prone Atlantic Coast Hurricane-prone Gulf Coast Interior-Point Method L-Shaped Method Short-term Disaster Warnings Solutions Two-Stage Stochastic Models Two-Stage Stochastic Programming |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00124479 |
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Graß, Emilia
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||
| Wiesbaden, : Springer Spektrum, 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
An Accelerated Solution Method for Two-Stage Stochastic Models in Disaster Management / Emilia Graß
| An Accelerated Solution Method for Two-Stage Stochastic Models in Disaster Management / Emilia Graß |
| Autore | Graß, Emilia |
| Edizione | [Wiesbaden : Springer Spektrum, 2018] |
| Pubbl/distr/stampa | xvii, 155 p., : ill. ; 24 cm |
| Descrizione fisica | Pubblicazione in formato elettronico |
| Soggetto topico |
90C90 - Applications of mathematical programming [MSC 2020]
90C51 - Interior-point methods [MSC 2020] 90C15 - Stochastic programming [MSC 2020] 90B50 - Management decision making, including multiple objectives [MSC 2020] 90-XX - Operations research, mathematical programming [MSC 2020] 90C59 - Approximation methods and heuristics in mathematical programming [MSC 2020] |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-SUN0124479 |
|
Graß, Emilia
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| xvii, 155 p., : ill. ; 24 cm | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Bayesian and High-Dimensional Global Optimization / Anatoly Zhigljavsky, Antanas Žilinskas
| Bayesian and High-Dimensional Global Optimization / Anatoly Zhigljavsky, Antanas Žilinskas |
| Autore | Zhigljavsky, Anatoly |
| Pubbl/distr/stampa | Cham, : Springer, 2021 |
| Descrizione fisica | viii, 118 p. : ill. ; 24 cm |
| Altri autori (Persone) | Žilinskas, Antanas |
| Soggetto topico |
90C15 - Stochastic programming [MSC 2020]
62F15 - Bayesian inference [MSC 2020] 90-XX - Operations research, mathematical programming [MSC 2020] 90C26 - Nonconvex programming, global optimization [MSC 2020] 65K05 - Numerical mathematical programming methods [MSC 2020] 90C59 - Approximation methods and heuristics in mathematical programming [MSC 2020] |
| Soggetto non controllato |
Bayesian global optimization
Expensive black-box functions Global optimization Global random search High-dimensional optimization Matrix theory Multidimensional spaces and sets P-algorithm |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0274585 |
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Zhigljavsky, Anatoly
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| Cham, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Bayesian and High-Dimensional Global Optimization / Anatoly Zhigljavsky, Antanas Žilinskas
| Bayesian and High-Dimensional Global Optimization / Anatoly Zhigljavsky, Antanas Žilinskas |
| Autore | Zhigljavsky, Anatoly A. |
| Pubbl/distr/stampa | Cham, : Springer, 2021 |
| Descrizione fisica | viii, 118 p. : ill. ; 24 cm |
| Altri autori (Persone) | Žilinskas, Antanas |
| Soggetto topico |
62F15 - Bayesian inference [MSC 2020]
65K05 - Numerical mathematical programming methods [MSC 2020] 90-XX - Operations research, mathematical programming [MSC 2020] 90C15 - Stochastic programming [MSC 2020] 90C26 - Nonconvex programming, global optimization [MSC 2020] 90C59 - Approximation methods and heuristics in mathematical programming [MSC 2020] |
| Soggetto non controllato |
Bayesian Global Optimization
Expensive black-box functions Global optimization Global random search High-dimensional optimization Matrix theory Multidimensional spaces and sets P-algorithm |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00274585 |
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Zhigljavsky, Anatoly A.
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| Cham, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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BONUS algorithm for large scale stochastic nonlinear programming problems / Urmila Diwekar, Amy David
| BONUS algorithm for large scale stochastic nonlinear programming problems / Urmila Diwekar, Amy David |
| Autore | Diwekar, Urmila M. |
| Pubbl/distr/stampa | New York, : Springer, 2015 |
| Descrizione fisica | XVIII, 146 p. : ill. ; 24 cm |
| Altri autori (Persone) | David, Amy |
| Soggetto topico |
90C15 - Stochastic programming [MSC 2020]
90C06 - Large-scale problems in mathematical programming [MSC 2020] |
| Soggetto non controllato |
BONUS algorithm
Power systems SNLP Sensor placement Stochastic Programming Water management |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ita |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0113101 |
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Diwekar, Urmila M.
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| New York, : Springer, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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BONUS algorithm for large scale stochastic nonlinear programming problems / Urmila Diwekar, Amy David
| BONUS algorithm for large scale stochastic nonlinear programming problems / Urmila Diwekar, Amy David |
| Autore | Diwekar, Urmila M. |
| Pubbl/distr/stampa | New York, : Springer, 2015 |
| Descrizione fisica | XVIII, 146 p. : ill. ; 24 cm |
| Altri autori (Persone) | David, Amy |
| Soggetto topico |
90C06 - Large-scale problems in mathematical programming [MSC 2020]
90C15 - Stochastic programming [MSC 2020] |
| Soggetto non controllato |
Bonus Algorithm
Power Systems SNLP Sensor placement Stochastic Programming Water Management |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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. |
| Record Nr. | UNICAMPANIA-VAN00113101 |
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Diwekar, Urmila M.
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| New York, : Springer, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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