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Titlebook: Uncertainty Management in Simulation-Optimization of Complex Systems; Algorithms and Appli Gabriella Dellino,Carlo Meloni Book 2015 Springe

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書(shū)目名稱(chēng)Uncertainty Management in Simulation-Optimization of Complex Systems
副標(biāo)題Algorithms and Appli
編輯Gabriella Dellino,Carlo Meloni
視頻videohttp://file.papertrans.cn/942/941092/941092.mp4
概述Presents the state of the art in computer-based simulation.Multidisciplinary contributors are leading names in the field.Presents real-world applications along with the latest research?
叢書(shū)名稱(chēng)Operations Research/Computer Science Interfaces Series
圖書(shū)封面Titlebook: Uncertainty Management in Simulation-Optimization of Complex Systems; Algorithms and Appli Gabriella Dellino,Carlo Meloni Book 2015 Springe
描述?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, especia
出版日期Book 2015
關(guān)鍵詞Bootstrapping; Kriging; Metamodeling; Simulation optimization; Stochastic; Uncertainty
版次1
doihttps://doi.org/10.1007/978-1-4899-7547-8
isbn_softcover978-1-4899-7961-2
isbn_ebook978-1-4899-7547-8Series ISSN 1387-666X Series E-ISSN 2698-5489
issn_series 1387-666X
copyrightSpringer Science+Business Media New York 2015
The information of publication is updating

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Supporting Time-Critical Decision Making with Real Time Simulationsvision of a fire and rescue service response to an emergency. The methodology of using a simulation model in this way is discussed using either a fully normal, or a partially normal statistical model. Two numerical examples are included including one from the fire and rescue service.
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Supporting Time-Critical Decision Making with Real Time Simulationsailable that can be made run sufficiently quickly then RSO can be used to aid time-critical decision making. An example of such a situation is the provision of a fire and rescue service response to an emergency. The methodology of using a simulation model in this way is discussed using either a full
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Book 2015mances 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 communiti
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Book 2015deling, 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, especia
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ert werden. Des weiteren enthalten die pr?operativen Planungen, die zumeist an einem Standardr?ntgenbild durchgeführt werdin, durch unbekannte Abweichungen von der Projektionsebene oder Verzerrungen des R?ntgenbildes ein Fehler-potential.
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