Fuzzy Stochastic Optimization

Theory, Models and Applications

  • Shuming Wang
  • Junzo Watada

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Shuming Wang, Junzo Watada
    Pages 1-5
  3. Theory

    1. Front Matter
      Pages 7-7
    2. Shuming Wang, Junzo Watada
      Pages 9-54
    3. Shuming Wang, Junzo Watada
      Pages 55-82
  4. Models

    1. Front Matter
      Pages 83-83
  5. Real-Life Applications

    1. Front Matter
      Pages 199-199
    2. Shuming Wang, Junzo Watada
      Pages 201-213
    3. Shuming Wang, Junzo Watada
      Pages 215-225
  6. Back Matter
    Pages 239-248

About this book

Introduction

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.









Keywords

Fuzzy Optimization Fuzzy Random Variable Industrial Informatics Intelligent Computation Management Engineering Meta-heuristics Operational Research Renewal Process Renewal Reward Process

Authors and affiliations

  • Shuming Wang
    • 1
  • Junzo Watada
    • 2
  1. 1.Waseda UniversityFukuokaJapan
  2. 2.Waseda UniversityFukuokaJapan

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4419-9560-5
  • Copyright Information Springer Science+Business Media New York 2012
  • Publisher Name Springer, Boston, MA
  • eBook Packages Engineering
  • Print ISBN 978-1-4419-9559-9
  • Online ISBN 978-1-4419-9560-5
  • About this book