Several Intuitionistic Fuzzy Multi-Attribute Decision Making Methods and Their Applications (Uncertainty and Operations Research)

This book introduces readers to the latest advances in and approaches to intuitionistic fuzzy decision-making methods. To do so, it explores a range of applications to practical decision-making problems, together with representative case studies. Examining a host of decision-making methods, most of which are based on intuitionistic fuzzy aggregation operators, its goal is to offer readers a new way to study decision-making methods in the intuitionistic fuzzy environment. Chiefly intended for practitioners and researchers working in the areas of risk management, decision-making under uncertainty, and operational research, the book can also be used as supplementary material for graduate and senior undergraduate courses in these areas. Preface 6 Contents 8 1 Introduction 11 1.1 Intuitionistic Fuzzy Set 11 1.2 Basic Operation Laws and Aggregation Operators 13 1.3 Content Design 15 References 16 2 The Decision Making Method Based on the New Distance Measure and Similarity Measure 18 2.1 Review of the Related Work 18 2.2 Distance and Similarity Measures for IFSs 20 2.3 Psychological Distance for IFSs 21 2.3.1 Psychological Distance 21 2.3.2 Psychological Distance Measure for IFNs 23 2.3.3 Psychological Distance Measure for IFSs 28 2.4 Similarity Measure for IFSs Based on the Psychological Distance 30 2.5 Extended Intuitionistic Fuzzy TOPSIS Method by the New Distance Measure 33 2.5.1 Algorithm of the Extended TOPSIS Method 33 2.5.2 Case Study of the Marine Energy Transportation Route Decision Making Problem 35 2.6 Remarks 40 References 41 3 The Dynamic Decision Making Method Based on the Intuitionistic Fuzzy Bayesian Network 43 3.1 Dynamic Decision Making Problems Under the Emergencies 43 3.2 Conceptual Framework for Dynamic Intuitionistic Fuzzy Decision Making 46 3.3 Intuitionistic Fuzzy Bayesian Network 47 3.3.1 Intuitionistic Fuzzy Event Under the Bayesian Network 48 3.3.2 Probability Transmissibility of the Intuitionistic Fuzzy Bayesian Network 49 3.4 Dynamic Intuitionistic Fuzzy Decision Making Model 52 3.4.1 Weight Determination Method in the Framework of IFBNs 52 3.4.2 Dynamic IFBN Decision Making Method 55 3.5 Applications to Mine Emergent Accident 59 3.6 Remarks 68 References 69 4 Novel Intuitionistic Fuzzy Decision Making Models in the Framework of Decision Field Theory 71 4.1 Decision Making Methods Based on the Aggregation Operators 71 4.2 The Intuitionistic Fuzzy Decision Making Model Based on the DFT 73 4.2.1 Introduction of the DFT 74 4.2.2 Integrated Intuition Fuzzy Decision Making Model Based on the DFT 76 4.2.3 Integrated Intuition Fuzzy Group Decision Making Model Based on the DFT 79 4.3 The Application of the Intuitionistic Fuzzy Decision Making Model Based on the DFT 82 4.3.1 Validation and Comparison for the Cognitive Decision Behavior 82 4.3.2 Application to the Decision Making of the Optimal Investment Country 88 4.4 Remarks 92 References 93 5 The Decision Making Method Under the Probabilistic and Cognitive Environment 95 5.1 Motivations and Background 95 5.2 Preliminaries 98 5.2.1 Dual Hesitant Fuzzy Set 98 5.2.2 Basic Operations of DHFEs 98 5.3 Probabilistic Dual Hesitant Fuzzy Sets 99 5.3.1 Concept of PDHFS 99 5.3.2 Comparison Method of PDHFEs 101 5.3.3 Basic Operations of PDHFEs 102 5.4 Information Aggregation and Visualization of PDHFSs 107 5.4.1 Basic Aggregation Operator for PDHFSs 107 5.4.2 Visualization of the PDHFS Based on the Cloud Model 110 5.5 Application to the Arctic Geopolitics Risk Evaluations 114 5.6 Remarks 117 References 118 Appendix A 120 References 122 Appendix B 123