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

Description

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 Contents 1 Introduction 1.1 Intuitionistic Fuzzy Set 1.2 Basic Operation Laws and Aggregation Operators 1.3 Content Design References 2 The Decision Making Method Based on the New Distance Measure and Similarity Measure 2.1 Review of the Related Work 2.2 Distance and Similarity Measures for IFSs 2.3 Psychological Distance for IFSs 2.3.1 Psychological Distance 2.3.2 Psychological Distance Measure for IFNs 2.3.3 Psychological Distance Measure for IFSs 2.4 Similarity Measure for IFSs Based on the Psychological Distance 2.5 Extended Intuitionistic Fuzzy TOPSIS Method by the New Distance Measure 2.5.1 Algorithm of the Extended TOPSIS Method 2.5.2 Case Study of the Marine Energy Transportation Route Decision Making Problem 2.6 Remarks References 3 The Dynamic Decision Making Method Based on the Intuitionistic Fuzzy Bayesian Network 3.1 Dynamic Decision Making Problems Under the Emergencies 3.2 Conceptual Framework for Dynamic Intuitionistic Fuzzy Decision Making 3.3 Intuitionistic Fuzzy Bayesian Network 3.3.1 Intuitionistic Fuzzy Event Under the Bayesian Network 3.3.2 Probability Transmissibility of the Intuitionistic Fuzzy Bayesian Network 3.4 Dynamic Intuitionistic Fuzzy Decision Making Model 3.4.1 Weight Determination Method in the Framework of IFBNs 3.4.2 Dynamic IFBN Decision Making Method 3.5 Applications to Mine Emergent Accident 3.6 Remarks References 4 Novel Intuitionistic Fuzzy Decision Making Models in the Framework of Decision Field Theory 4.1 Decision Making Methods Based on the Aggregation Operators 4.2 The Intuitionistic Fuzzy Decision Making Model Based on the DFT 4.2.1 Introduction of the DFT 4.2.2 Integrated Intuition Fuzzy Decision Making Model Based on the DFT 4.2.3 Integrated Intuition Fuzzy Group Decision Making Model Based on the DFT 4.3 The Application of the Intuitionistic Fuzzy Decision Making Model Based on the DFT 4.3.1 Validation and Comparison for the Cognitive Decision Behavior 4.3.2 Application to the Decision Making of the Optimal Investment Country 4.4 Remarks References 5 The Decision Making Method Under the Probabilistic and Cognitive Environment 5.1 Motivations and Background 5.2 Preliminaries 5.2.1 Dual Hesitant Fuzzy Set 5.2.2 Basic Operations of DHFEs 5.3 Probabilistic Dual Hesitant Fuzzy Sets 5.3.1 Concept of PDHFS 5.3.2 Comparison Method of PDHFEs 5.3.3 Basic Operations of PDHFEs 5.4 Information Aggregation and Visualization of PDHFSs 5.4.1 Basic Aggregation Operator for PDHFSs 5.4.2 Visualization of the PDHFS Based on the Cloud Model 5.5 Application to the Arctic Geopolitics Risk Evaluations 5.6 Remarks References Appendix A References Appendix B