Lectures on stochastic programming : modeling and theory

Bibliographic Information

Lectures on stochastic programming : modeling and theory

Alexander Shapiro, Darinka Dentcheva, Andrzej Ruszczyński

(MOS-SIAM series on optimization, 28)

Society for Industrial and Applied Mathematics, 2021

3rd ed

  • : hbk

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Note

Includes bibliographical references and index

Description and Table of Contents

Description

Lectures on Stochastic Programming: Modeling and Theory, Third Edition covers optimization problems involving uncertain parameters for which stochastic models are available. These problems occur in almost all areas of science and engineering. This substantial revision of the previous edition presents a modern theory of stochastic programming, including expanded coverage of sample complexity, risk measures, and distributionally robust optimization: Chapter 6 is updated and the interchangeability principle for risk measures is discussed in detail. Two new chapters, 'Distributionally Robust Stochastic Programming' (DRSP) and 'Computational Methods' provide readers with a solid understanding of emerging topics. Chapter 8 presents new material on formulation and numerical approaches to solving periodical multistage stochastic programs. This book is written for researchers and graduate students working on theory and applications of optimization.

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Details

  • NCID
    BC18292549
  • ISBN
    • 9781611976588
  • Country Code
    us
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Philadelphia
  • Pages/Volumes
    xv, 525 p.
  • Size
    26 cm
  • Classification
  • Subject Headings
  • Parent Bibliography ID
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