uncertainty management simulation optimization complex (23 résultats)

Hardcover. Etat : Wie neu. New book, remains sealed in plastic. Language - English. Ships from Berlin.

Etat : New. In.

Etat : New.

Hardcover. Etat : Brand New. 9.25x6.25x0.75 inches. In Stock.

Taschenbuch. Etat : Neu. Uncertainty Management in Simulation-Optimization of Complex Systems | Algorithms and Applications | Gabriella Dellino (u. a.) | Taschenbuch | Operations Research/Computer Science Interfaces Series | xviii | Englisch | 2016 | Springer | EAN 9781489979612 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issues in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from slightly different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others. This editorial project brings together - as chapter contributors - researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. Editors' goal is to take advantage of such a multidisciplinary environment, to offer to the readers a much deeper understanding of the commonalities and differences of the various approaches to simulation-based optimization, especially in uncertain environments. Editors aim to offer a bibliographic reference on the topic, enabling interested readers to learn about the state-of-the-art in this research area, also accounting for potential real-world applications to improve also the state-of-the-practice. Besides researchers and scientists of the field, the primary audience for the proposed book includes PhD students, academic teachers, as well as practitioners and professionals. Each of these categories of potential readers present adequate channels for marketing actions, e.g. scientific, academic or professional societies, internet-based communities, and authors or buyers of related publications.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issues in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from slightly different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others. This editorial project brings together - as chapter contributors - researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. Editors' goal is to take advantage of such a multidisciplinary environment, to offer to the readers a much deeper understanding of the commonalities and differences of the various approaches to simulation-based optimization, especially in uncertain environments. Editors aim to offer a bibliographic reference on the topic, enabling interested readers to learn about the state-of-the-art in this research area, also accounting for potential real-world applications to improve also the state-of-the-practice. Besides researchers and scientists of the field, the primary audience for the proposed book includes PhD students, academic teachers, as well as practitioners and professionals. Each of these categories of potential readers present adequate channels for marketing actions, e.g. scientific, academic or professional societies, internet-based communities, and authors or buyers of related publications.

Paperback. Etat : Brand New. reprint edition. 289 pages. 9.25x6.10x0.69 inches. In Stock.

Hardcover. Etat : Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Etat : New. pp. 292.

Paperback. Etat : Like New. Like New. Ships from Multiple Locations. book.

Etat : new. Questo è un articolo print on demand.

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issues in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from slightly different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others. This editorial project brings together - as chapter contributors - researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. Editors' goal is to take advantage of such a multidisciplinary environment, to offer to the readers a much deeper understanding of the commonalities and differences of the various approaches to simulation-based optimization, especially in uncertain environments. Editors aim to offer a bibliographic reference on the topic, enabling interested readers to learn about the state-of-the-art in this research area, also accounting for potential real-world applications to improve also the state-of-the-practice. Besides researchers and scientists of the field, the primary audience for the proposed book includes PhD students, academic teachers, as well as practitioners and professionals. Each of these categories of potential readers present adequate channels for marketing actions, e.g. scientific, academic or professional societies, internet-based communities, and authors or buyers of related publications. 292 pp. Englisch.

Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issues in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from slightly different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others. This editorial project brings together - as chapter contributors - researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. Editors' goal is to take advantage of such a multidisciplinary environment, to offer to the readers a much deeper understanding of the commonalities and differences of the various approaches to simulation-based optimization, especially in uncertain environments. Editors aim to offer a bibliographic reference on the topic, enabling interested readers to learn about the state-of-the-art in this research area, also accounting for potential real-world applications to improve also the state-of-the-practice. Besides researchers and scientists of the field, the primary audience for the proposed book includes PhD students, academic teachers, as well as practitioners and professionals. Each of these categories of potential readers present adequate channels for marketing actions, e.g. scientific, academic or professional societies, internet-based communities, and authors or buyers of related publications. 292 pp. Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the state of the art in computer-based simulationMultidisciplinary contributors are leading names in the fieldPresents real-world applications along with the latest researchGabriella Dellino graduated in Computer .

Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the state of the art in computer-based simulationMultidisciplinary contributors are leading names in the fieldPresents real-world applications along with the latest researchGabriella Dellino graduated in Computer .

Etat : New. Print on Demand.

Buch. Etat : Neu. Uncertainty Management in Simulation-Optimization of Complex Systems | Algorithms and Applications | Gabriella Dellino (u. a.) | Buch | Operations Research/Computer Science Interfaces Series | xviii | Englisch | 2015 | Springer | EAN 9781489975461 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Etat : New. PRINT ON DEMAND.

Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -¿This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issues in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from slightly different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others. This editorial project brings together ¿ as chapter contributors ¿ researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. Editors¿ goal is to take advantage of such a multidisciplinary environment, to offer to the readers a much deeper understanding of the commonalities and differences of the various approaches to simulation-based optimization, especially in uncertain environments. Editors aim to offer a bibliographic reference on the topic, enabling interested readers to learn about the state-of-the-art in this research area, also accounting for potential real-world applications to improve also the state-of-the-practice. Besides researchers and scientists of the field, the primary audience for the proposed book includes PhD students, academic teachers, as well as practitioners and professionals. Each of these categories of potential readers present adequate channels for marketing actions, e.g. scientific, academic or professional societies, internet-based communities, and authors or buyers of related publications.¿Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 292 pp. Englisch.

Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -¿This book aims at illustrating strategies to account for uncertainty in complex systems described by computer simulations. When optimizing the performances of these systems, accounting or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issues in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from slightly different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others. This editorial project brings together ¿ as chapter contributors ¿ researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. Editors¿ goal is to take advantage of such a multidisciplinary environment, to offer to the readers a much deeper understanding of the commonalities and differences of the various approaches to simulation-based optimization, especially in uncertain environments. Editors aim to offer a bibliographic reference on the topic, enabling interested readers to learn about the state-of-the-art in this research area, also accounting for potential real-world applications to improve also the state-of-the-practice. Besides researchers and scientists of the field, the primary audience for the proposed book includes PhD students, academic teachers, as well as practitioners and professionals. Each of these categories of potential readers present adequate channels for marketing actions, e.g. scientific, academic or professional societies, internet-based communities, and authors or buyers of related publications.¿Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 292 pp. Englisch.

Etat : New. Print on Demand pp. 292.

Etat : New. PRINT ON DEMAND pp. 292.