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Fuzzy Stochastic Optimization: Theory, Models and Applications by Junzo Watada, Shuming Wang (Paperback, 2014)

About this product

About this product

Product Information

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.

Product Identifiers

Publisher
Springer-Verlag New York Inc.
ISBN-13
9781489992734
eBay Product ID (ePID)
209256789

Product Key Features

Author
Junzo Watada, Shuming Wang
Publication Name
Fuzzy Stochastic Optimization: Theory, Models and Applications
Format
Paperback
Language
English
Subject
Computer Science, Mathematics
Publication Year
2014
Type
Textbook
Number of Pages
248 Pages

Dimensions

Item Height
235mm
Item Width
155mm
Item Weight
409g

Additional Product Features

Title_Author
Junzo Watada, Shuming Wang
Country/Region of Manufacture
United States

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