Fuzzy Stochastic Optimization
Wang, Shuming; Watada, Junzo
€ 128.48
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Description for Fuzzy Stochastic Optimization
Hardback. This book looks at the framework of the fuzzy random optimization including theoretical results, optimization models, intelligent algorithms, and case studies. It presents how to design the solution algorithms to these fuzzy random optimization problems. Num Pages: 248 pages, 43 black & white tables, biography. BIC Classification: PBT; PBU; UYQ. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 15. Weight in Grams: 561.
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 ... Read more
Product Details
Format
Hardback
Publication date
2012
Publisher
Springer-Verlag New York Inc. United States
Number of pages
248
Condition
New
Number of Pages
248
Place of Publication
New York, NY, United States
ISBN
9781441995599
SKU
V9781441995599
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Wang, Shuming; Watada, Junzo
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 ... Read more
Reviews for Fuzzy Stochastic Optimization
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)