Fuzzy Stochastic Optimization

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 Associate Editor of various international journals, including International Journal of Biomedical Soft Computing and Human Sciences, ICIC Express Letters, International Journal of Systems and Control Engineering, and Fuzzy Optimization & Decision Making.

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." (Robert Fuller, Mathematical Reviews, January, 2013)

• Part I: Theory.- Fuzzy Random Variable.- Fuzzy Stochastic Renewal Processes.- Part II: Models.- System Reliability Optimization Models with Fuzzy Random Lifetimes.- Recourse-Based Fuzzy Random Facility Location Model with Fixed Capacity.- Two-Stage Fuzzy Stochastic Programming with Value-at-Risk: A Generic Model.- VaR-Based Fuzzy Random Facility Location Model with Variable Capacity.- Part III: Real-Life Applications.