Preface 1
Chapter 1. Introduction 1
1.1 Background 1
1.1.1 Development of bounded rationality 2
1.1.2 Development of fuzzy information 3
1.1.3 Importance of research about fuzzy decision making with prospect theory 3
1.2 Corresponding preliminaries 4
1.2.1 Prospect theory 5
1.2.2 TODIM 5
1.2.3 Intuitionistic fuzzy information 7
1.2.4 Probabilistic hesitant fuzzy information 9 1.2.5 Hesitant fuzzy linguistic information 11
1.2.6 Probabilistic linguistic information 14
1.3 Aim and focus of this book 17
Chapter 2. Intuitionistic Fuzzy MADM based on PT 19
2.1 Decision-making procedure 20
2.2 Illustrative example 24
2.2.1 Decision-making attributes used by VCs 26
2.2.2 Selecting process and results derived by IFPT 28
2.2.3. Selecting process and results derived by TOPSIS 30
2.3. Remarks 33
Chapter 3. QUALIFLEX based on PT with Probabilistic Linguistic Information 35 3.1 Procedure of P-QUALIFLEX with probabilistic linguistic information 36
3.2 Procedure of the extended QUALIFLEX with probabilistic linguistic information 39
3.3 Illustrative example 41
3.3.1 Results of P-QUALIFLEX with probabilistic linguistic information 42 3.3.2 Results of the extended QUALIFLEX with probabilistic linguistic information 46
3.4 Comparative analysis 48
3.4.1 Comparison of P-QUALIFLEX with extended QUALIFLEX 48
3.4.2 Comparison of P-QUALIFLEX with TODIM 50
3.5 Remarks 55
Chapter 4. Group PROMETHEE based on PT with Hesitant Fuzzy Linguistic Information 57
4.1 GP-PROMETHEE with hesitant fuzzy linguistic information 60 4.2 G-PROMETHEE with hesitant fuzzy linguistic information 65
4.3 Illustrative example 67
4.3.1 Decision-making background 67
4.3.2 Results of the GP-PROMETHEE with hesitant fuzzy linguistic information 69 4.3.3 Results of the G-PROMETHEE with hesitant fuzzy linguistic information 75
4.3.4 Results of TODIM with hesitant fuzzy linguistic information 78
4.3.5 Comparative analysis 80 4.3.5.1 Comparative analysis based on the results of illustrative example 81
4.3.5.2 Comparative analysis based on the sensitivity of parameters 82
4.4 Simulation analysis 88
4.5 Remarks 91
Chapter 5. Prospect Consensus with Probabilistic Hesitant Fuzzy Preference Information
About the Author:
Xiaoli Tian is Associate Professor of the School of Business Administration in Southwestern University of Finance and Economics, Chengdu, China. She was Academic Visitor with the Department of Computer Science and Artificial Intelligence, University of Granada, Spain, in 2017. She has published more than 15 peer-reviewed papers, many in high-quality international journals including Knowledge-Based Systems, Applied Soft Computing, Technological and Economic Development of Economy, Technological Forecasting and Social Change, etc. One of her papers has been selected as ESI Highly Cited Papers. Her current research interest includes large-scale consensus, group decision making, decision making with bounded rationality, and multiple attributes decision making under uncertainty. Dr. Tian serves as a reviewer for more than 10 international journals.
Zeshui Xu is Distinguished Young Scholar of the National Natural Science Foundation of China and Chang Jiang Scholars of the Ministry of Education of China. He is currently Professor with the Business School, Sichuan University, Chengdu, China. He has been elected as Academician of IASCYS (International academy for systems and cybernetic sciences), Fellow of IEEE (Institute of Electrical and Electronics Engineers), Fellow of IFSA (International Fuzzy Systems Association), Fellow of RSA (Royal Society of Arts), Fellow of IET (Institution of Engineering and Technology), Fellow of BCS (British Computer Society), Fellow of IAAM (International Association of Advanced Materials), Fellow of VEBLEO, and ranked 431th among World's Top 100,000 Scientists in 2019. He has contributed more than 600 SCI/SSCI articles to professional journals, and is among the world's top 1% most highly cited researchers with about 62,000 citations, his h-index is 123. He is currently the Associate Editors of IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, IEEE Access, Information Sciences, Fuzzy Optimization and Decision Making, Journal of the Operational Research Socitey, International Journal of Systems Science, Artificial Intelligence Review, etc. His current research interests include decision making, information fusion, data analysis, fuzzy systems and applications.
