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Uncertainty Management in Simulation-Optimization of Complex Systems: Algorithms and Applications
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, shastic 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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Uncertainty Management in Simulation-Optimization of Complex Systems: Algorithms and Applications
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, shastic 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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Uncertainty Management in Simulation-Optimization of Complex Systems: Algorithms and Applications

Uncertainty Management in Simulation-Optimization of Complex Systems: Algorithms and Applications

Uncertainty Management in Simulation-Optimization of Complex Systems: Algorithms and Applications

Uncertainty Management in Simulation-Optimization of Complex Systems: Algorithms and Applications

Overview

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, shastic 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.​

Product Details

ISBN-13: 9781489975461
Publisher: Springer US
Publication date: 06/30/2015
Series: Operations Research/Computer Science Interfaces Series , #59
Edition description: 2015
Pages: 271
Product dimensions: 6.10(w) x 9.25(h) x (d)

About the Author

Gabriella Dellino graduated in Computer Science Engineering at the Polytechnic of Bari, in 2005. In 2009 she earned her Ph.D. in Applied Mathematics from the University of Bari. During the Ph.D. she was a visiting fellow at the CentER – Tilburg School of Economics and Management (The Netherlands). Then she joined the research group of Decision and Management Methods of the University of Siena, while in 2011 she became assistant professor in Management Science at IMT Institute for Advanced Studies (Lucca). Currently, she works at the Istituto per le Applicazioni del Calcolo “Mauro Picone” of the National Research Council of Italy.

Throughout these years she has been involved in several national and international research projects funded by academic organizations and private companies, including the recent cooperation in the FP7 STAR*AgroEnergy research project, led by University of Foggia.

Her research mostly focuses on designing mathematical models and computer simulation models for complex systems investigation, with a specific focus on metamodeling approaches and uncertainty management, the final aim being the development of a Decision Support System, supporting managers and stakeholders from the relevant domain(s) in their decision-making processes. Applications of the designed methodological frameworks spread from engineering to management, economics and health care. This research activity resulted in several publications on international journals and books.

Carlo Meloni is an Assistant Professor of Systems Engineering and Optimization at the Politecnico di Bari (Italy). His main research and professional interests concern the theory and the applications of optimization, simulation and other OR/MS methodologies.

He took part in research projects promoted by the MIUR (Italian Ministry of Education, University and Research), academy, research centers, companies and organizations from both for-profit andnonprofit sectors. His works have been presented in several international conferences and published on different international journals and volumes. Carlo Meloni is member of the Italian Society of Operations Research (AIRO), INFORMS (The Institute for Operations Research and the Management Sciences), and IMACS (International Association for Mathematics and Computers in Simulation). He is also active in different EURO (The Association of European Operational Research Societies) working groups.

Currently, he is a researcher affiliated with INDAM (Istituto Nazionale di Alta Matematica “F. Severi”, Italy) and CNR-IAC (Istituto per le Applicazioni del Calcolo “M. Picone”, Italy).

Table of Contents

Part I: Advanced Tutorials.- Supporting Time-Critical Decision Making with Real Time Simulations.- Metamodel-based Robust Simulation-Optimization: An Overview.- Simulation-Based Modelling of a Shastic Equilibrium.- Part II: Uncertainty Management Using Sequential Parameter Optimization.- A Review on Global Sensitivity Analysis Methods.- Connections Among Optimization Models with Uncertainties, ABC and RBV.- Addressing Uncertainty in Complex Systems. The Case of Bio-Based Products Derived from Urban Bio-Waste Valorisation.- Part III: Methods and Applications.- Global Optimization of Simulation Based Complex Systems.- Personnel Scheduling in Queues with Time-Varying Arrival Rates: Applications of Simulation-Optimization.- Shastic Dual Dynamic Programming Solution of a Short-Term Disaster Management Problem.- Optimal Sk Allocation in Single Echelon Inventory Systems Subject to a Service Constraint.
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