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Uncertainty Management in Simulation-Optimization of Complex Systems

Algorithms and Applications

  • Gabriella Dellino
  • Carlo Meloni

Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 59)

Table of contents

  1. Front Matter
    Pages i-xviii
  2. Advanced Tutorials

    1. Front Matter
      Pages 1-1
    2. Gabriella Dellino, Jack P. C. Kleijnen, Carlo Meloni
      Pages 27-54
  3. Uncertainty Management Approaches

    1. Front Matter
      Pages 77-77
    2. Thomas Bartz-Beielstein, Christian Jung, Martin Zaefferer
      Pages 79-99
    3. Bertrand Iooss, Paul Lemaître
      Pages 101-122
    4. Saverio Giuliani, Carlo Meloni
      Pages 123-149
  4. Methods and Applications

About this book

Introduction

This book illustrates strategies to account for uncertainty in complex systems as described by computer simulations. When optimizing the performances of these systems, accounting for or neglecting uncertainty may lead to completely different results; therefore, uncertainty management is a major issue in simulation-optimization. Because of its wide field of applications, simulation-optimization issues have been addressed by different communities with different methods, and from somewhat different perspectives. Alternative approaches have been developed, also depending on the application context, without any well-established method clearly outperforming the others.

The book brings together researchers from different (though interrelated) areas; namely, statistical methods, experimental design, stochastic programming, global optimization, metamodeling, and design and analysis of computer simulation experiments. The aim of this editorial work is to take advantage of such a multidisciplinary environment to give 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, while also accounting for potential real-world applications. Besides researchers and scientists in the field, the primary audience for the book includes Ph.D. students, academic teachers, and practitioners.

The editors have been the recipients of a European Science Foundation award (STRAT01-EW11-068) for the organization of the Strategic Workshop “Uncertainty management in simulation-optimization of complex systems: algorithms and applications”, held in Rome from 9th to 12th May 2012, which foster an in-depth trans-disciplinary discussion on the topic of this book.

Keywords

Bootstrapping Kriging Metamodeling Simulation optimization Stochastic Uncertainty

Editors and affiliations

  • Gabriella Dellino
    • 1
  • Carlo Meloni
    • 2
  1. 1.Istituto per le Applicazioni del Calcolo “Mauro Picone”, Consiglio Nazionale delle RicercheBariItaly
  2. 2.Dipartimento di Ingegneria Elettrica e dell’InformazionePolitecnico di BariBariItaly

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4899-7547-8
  • Copyright Information Springer Science+Business Media New York 2015
  • Publisher Name Springer, Boston, MA
  • eBook Packages Business and Economics
  • Print ISBN 978-1-4899-7546-1
  • Online ISBN 978-1-4899-7547-8
  • Series Print ISSN 1387-666X
  • Buy this book on publisher's site
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