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Uncertainty Management In Simulationoptimization Of Complex Systems Algorithms And Applications 1st Edition Gabriella Dellino

  • SKU: BELL-5139970
Uncertainty Management In Simulationoptimization Of Complex Systems Algorithms And Applications 1st Edition Gabriella Dellino
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Uncertainty Management In Simulationoptimization Of Complex Systems Algorithms And Applications 1st Edition Gabriella Dellino instant download after payment.

Publisher: Springer US
File Extension: PDF
File size: 5.26 MB
Pages: 271
Author: Gabriella Dellino, Carlo Meloni (eds.)
ISBN: 9781489975461, 1489975462
Language: English
Year: 2015
Edition: 1

Product desciption

Uncertainty Management In Simulationoptimization Of Complex Systems Algorithms And Applications 1st Edition Gabriella Dellino by Gabriella Dellino, Carlo Meloni (eds.) 9781489975461, 1489975462 instant download after payment.

​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.​

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