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Fuzzy Stochastic Optimization

Theory, Models and Applications

Authors: Wang, Shuming, Watada, Junzo

  • Examines statistical methods with fuzzy data based on the fuzzy random variable
  • Covers how to characterize information which is both probabilistically uncertain and fuzzily imprecise
  • Discusses building optimization models working with uncertain data
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  • ISBN 978-1-4419-9560-5
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About this book

In 2014, winner of "Outstanding Book Award" by The Japan Society for Fuzzy Theory and Intelligent Informatics.

Covering in detail both theoretical and practical perspectives, this book is a self-contained and systematic depiction of current fuzzy stochastic optimization that deploys the fuzzy random variable as a core mathematical tool to model the integrated fuzzy random uncertainty. It proceeds in an orderly fashion from the requisite theoretical aspects of the fuzzy random variable to fuzzy stochastic optimization models and their real-life case studies.

 

The volume reflects the fact that randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world, with significant implications in a number of settings. In industrial engineering, management and economics, the chances are high that decision makers will be confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and optimization in the form of a decision must be made in an environment that is doubly uncertain, characterized by a co-occurrence of randomness and fuzziness. This book begins by outlining the history and development of the fuzzy random variable before detailing numerous optimization models and applications that include the design of system controls for a dam.









About the authors

In 2014, winner of "Outstanding Book Award" by The Japan Society for Fuzzy Theory and Intelligent Informatics. Dr. Shuming Wang received his Ph.D in Engineering at WASEDA University, Japan, 2011. He was a Special Research Fellow of the Japan Society for the Promotion of Science (JSPS), Japan, and worked as a Researcher in Research Institute and Risk Management Division of China Galaxy Securities Co. LTD (HQ), Beijing, China. Currently, Dr. Wang is being with National University of Singapore (NUS) as a Research Fellow, he is also an Adjunct Researcher of WASEDA University, Japan.

Dr. Wang has published more than 20 international journal and conference papers in the fields of optimization under uncertainty, soft computing, and industrial engineering. He has also served as a referee for several international journals, including, IEEE Transactions on Systems, Man & Cybernetics: Systems, IEEE Transactions on Systems, Man & Cybernetics: Cybernetics, IEEE Transactions on Industrial Electronics, IEEE Transactions on Engineering Management, Annals of Operations Research, International Journal of Production Research, and Journal of Global Optimization.

Dr. Junzo Watada is currently a full professor of Management Engineering, Knowledge Engineering and Soft Computing at Graduate School of Information, Production & Systems, Waseda University. He is the Principal Editor, a Co-Editor and an A

ssociate Editor of various international journals, including International Journal of Biomedical Soft Computing and Human Sciences, ICIC Express Letters, International J

ournal of Systems and Control Engineering, and Fuzzy Optimization & Decision Making.

Reviews

From the reviews:

“Fuzzy stochastic optimization models can be divided into two main classes: single-stage and multistage models. The book consists of three parts: ‘Theory’, ‘Models’ and ‘Real-life applications’. … This book may be useful for students and researchers in uncertain programming.” (Róbert Fullér, Mathematical Reviews, January, 2013)


Table of contents (9 chapters)

  • Introduction

    Wang, Shuming (et al.)

    Pages 1-5

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  • Fuzzy Random Variable

    Wang, Shuming (et al.)

    Pages 9-54

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  • Fuzzy Stochastic Renewal Processes

    Wang, Shuming (et al.)

    Pages 55-82

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  • System Reliability Optimization Models with Fuzzy Random Lifetimes

    Wang, Shuming (et al.)

    Pages 85-116

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  • Recourse-Based Fuzzy Random Facility Location Model with Fixed Capacity

    Wang, Shuming (et al.)

    Pages 117-147

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Buy this book

eBook n/a
  • ISBN 978-1-4419-9560-5
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
Hardcover n/a
  • ISBN 978-1-4419-9559-9
  • Free shipping for individuals worldwide
Softcover n/a
  • ISBN 978-1-4899-9273-4
  • Free shipping for individuals worldwide
Rent the eBook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Fuzzy Stochastic Optimization
Book Subtitle
Theory, Models and Applications
Authors
Copyright
2012
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media New York
eBook ISBN
978-1-4419-9560-5
DOI
10.1007/978-1-4419-9560-5
Hardcover ISBN
978-1-4419-9559-9
Softcover ISBN
978-1-4899-9273-4
Edition Number
1
Number of Pages
XVI, 248
Topics