Fuzzy Stochastic Optimization - Theory, Models and Applications (Paperback, 2012 ed.)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Release date:	April 2014
First published:	2012
Authors:	Shuming Wang • Junzo Watada
Dimensions:	235 x 155 x 14mm (L x W x T)
Format:	Paperback
Pages:	248
Edition:	2012 ed.
ISBN-13:	978-1-4899-9273-4
Categories:	Books > Science & Mathematics > Mathematics > Optimization > General Books > Science & Mathematics > Mathematics > Applied mathematics > Stochastics
LSN:	1-4899-9273-1
Barcode:	9781489992734

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