Fuzzy and Multi-Level Decision Making: Soft Computing Approaches - Cheng, Chi-Bin

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Biographie:
Dr. Chi-Bin Cheng received his Ph.D. in Industrial and Manufacturing Systems Engineering from Kansas State University, USA. He is currently Professor in the Department of Information Management at Tamkang University, Taiwan. His primary research interests include artificial intelligence, machine learning, optimization, flight safety management, scheduling, and soft computing. Dr. Cheng has collaborated with EVA Air on flight safety research projects from 2009 to 2024, including the development of the Flight Operations Risk Assessment System (FORAS). He has published approximately 50 journal papers and co-authored a book titled Fuzzy and Multi-Level Decision Making: Soft Computing Approaches. Dr. Cheng has been recognized as one of the World's Top 2% Scientists (Career) by Stanford University and Elsevier for the years 2020-2023. Huan-Jyh Shyur received his Ph.D. from the Department of Industrial and Systems Engineering at Rutgers University. After earning his doctorate, he worked at the Federal Aviation Administration (FAA) Technical Center in the United States, where he led the SPAS (Safety Performance Analysis System) project. He is currently Full-Time Professor in the Department of Information Management at Tamkang University. During his tenure at Tamkang University, Dr. Shyur actively participated in aviation safety projects with the Civil Aeronautics Administration (CAA) of Taiwan and contributed to the development of the FORAS (Flight Operations Risk Assessment System) project in collaboration with EVA Air. His research interests include aviation safety management, reliability engineering, decision theory, and the application of artificial intelligence....

Sommaire:
This book offers a comprehensive overview of cutting-edge approaches for decision-making in hierarchical organizations. It presents soft-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these approaches can be effectively used to deal with problems typical of this kind of organization. After introducing the main classical approaches applied to multiple-level programming, the book describes a set of soft-computing techniques, demonstrating their advantages in providing more efficient solutions to hierarchical decision-making problems compared to the classical methods. Based on the book Fuzzy and Multi-Level Decision Making (Springer, 2001) by Lee E.S and Shih, H., this second edition has been expanded to include the most recent findings and methods and a broader spectrum of soft computing approaches. All the algorithms are presented in detail, together with a wealth of practical examplesand solutions to real-world problems, providing students, researchers and professionals with a timely, practice-oriented reference guide to the area of interactive fuzzy decision making, multi-level programming and hierarchical optimization....