Fuzzy Decision Analysis: Multi Attribute Decision Making Approach (Studies in Computational Intelligence, 1121)

✍ Scribed by Farhad Hosseinzadeh Lotfi, Tofigh Allahviranloo, Witold Pedrycz, Mohammadreza Shahriari, Hamid Sharafi, Somayeh Razipour GhalehJough

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 362
• Category: Library

✦ Synopsis

Authored by a leading expert in the field, this book introduces an innovative methodology that harnesses the power of fuzzy logic to enhance decision-making in multi-attribute scenarios. In a world of complexity and uncertainty, effective decision-making is paramount. Springer proudly presents a cutting-edge publication that revolutionizes decision analysis: "Fuzzy Decision Analysis: Multi-attribute Decision-Making Approach." This book stands at the forefront of decision analysis, introducing the integration of fuzzy logic into multi-attribute decision-making. It is a transformative journey into the realm of advanced decision analysis. It book not only equips you with the knowledge to comprehend the theoretical underpinnings but also empowers you to apply these insights in practical scenarios. This book serves as your indispensable companion. Its comprehensive coverage serves as a beacon, guiding you through the intricate maze of fuzzy logic and multi-attribute decision-making, ultimately empowering you to embrace innovation and master the art of making well-informed decisions in an ever-changing world.

✦ Table of Contents

Preface
Acknowledgements
Introduction
Contents
1 Foundations of Decision
1.1 Introduction
1.2 Decision Theory
1.3 Existential Philosophy of Decision Theory
1.4 Decision Science
1.5 The Importance and Applications of Decision Science
1.6 The Decision-Making Theories
1.7 The Reputable Domains and Applications of Decision Making
1.7.1 Decision Support Systems and Business Intelligence
1.7.2 Strategic Management
1.7.3 Healthcare and Medicine
1.7.4 Financial Decision-Making
1.7.5 Project Management and Scheduling
1.7.6 Environmental Planning and Management
1.7.7 Supply Chain and Operations Management
1.7.8 Engineering and Technology
1.7.9 Decision Making in Maintenance and Reliability
1.7.10 Human Resources and Talent Management
1.7.11 Crisis Management and Emergency Response
1.7.12 Public Policy and Governance
1.7.13 The Application of Decision Making Would Not End to Mentioned Area
1.8 The Reputable and Helpful Models and Techniques of Decision Making
1.8.1 Rational Decision-Making Model
1.8.2 Decision Trees
1.8.3 Cost–Benefit Analysis
1.8.4 SWOT Analysis
1.8.5 Pareto Analysis
1.8.6 Linear Programming (LP), Non-Linear Programming (NLP), and Integer Programming (IP)
1.8.7 Queuing Theory
1.8.8 Simulation Approaches
1.8.9 Data Envelopment Analysis (DEA)
1.9 The Hierarchy of Decisions
1.10 A Historical Review About Decision Making
1.11 Multi Attribute Decision Making (MADM)
1.11.1 Multi-Criteria Decision-Making Problems
1.11.2 Multi-Objective Decision-Making Problems
1.11.3 Design Models in Conditions of Uncertainty
1.12 Scale Measurements of Data
1.13 Qualitative Data and Ordinal Numbers
1.14 Quantitative Data and Cardinal Numbers
1.15 Scientometrics in the field of Fuzzy Multi Attribute Decision Making
1.16 Conclusion
References
2 Fuzzy Introductory Concepts
2.1 Introduction
2.2 Fuzzy Set Theory: Basic Concepts
2.3 Ranking of Fuzzy Numbers
2.3.1 Fuzzy Number Ranking Based on α-Cuts
2.3.2 Fuzzy Number Ranking Based on Hamming Distance
2.4 Type-2 Fuzzy Numbers
2.5 Type-2 Trapezoidal and Triangular Fuzzy Numbers
2.5.1 Arithmetic Operations on Type-2 Trapezoidal Fuzzy Numbers
2.5.2 Arithmetic Operations on Type-2 Triangular Fuzzy Numbers
2.6 Ranking of Type-2 Interval Fuzzy Numbers
2.6.1 Some Ranking Methods for Type-2 Interval Fuzzy Numbers
2.7 Conclusions
References
3 Weight Determination Methods in Fuzzy Environment
3.1 Introduction
3.2 Fuzzy Approximation Methods
3.2.1 Fuzzy Row Sum Method
3.2.2 Fuzzy Column Sum Method
3.2.3 Fuzzy Geometric Mean Method
3.3 Fuzzy Shannon Entropy Method
3.3.1 Shannon Entropy Method Using Triangular Fuzzy Number
3.4 Fuzzy Least Squares Method
3.5 BWM Method
3.5.1 Fuzzy BWM
3.6 Conclusion
References
4 Non-Compensatory Methods in Uncertainty Environment
4.1 Introduction: Non-Compensatory Fuzzy Methods
4.2 Fuzzy Lexicographic Method
4.3 Fuzzy Dominance Method
4.4 Fuzzy Max–Min Method
4.5 Fuzzy Conjunctive Satisfying Method
4.6 Fuzzy Disjunction Satisfying Method
4.7 Conclusion
References
5 Simple Additive Weighting (SAW) Method in Fuzzy Environment
5.1 Introduction
5.2 SAW Method
5.3 Choosing a Hospital Location
5.4 SAW Method in Imprecise Environments
5.5 Interval SAW
5.5.1 The First Approach of Interval SAW
5.5.2 The Second Approach of SAW-Interval Method
5.5.3 Application of Interval SAW Method
5.5.4 Fuzzy SAW
5.5.5 Fuzzy SAW Method with Predetermined Weights
5.5.6 Fuzzy SAW Method with Unknown Weights
5.5.7 Fuzzy SAW Application
5.6 Conclusion
References
6 Technique for Order Preferences by Similarity to Ideal Solutions (TOPSIS) in Uncertainty Environment
6.1 Introduction: The Essence of the TOPSIS Method and Its Application
6.2 Description of the TOPSIS Method
6.2.1 Case Study
6.3 Fuzzy TOPSIS Method Using Triangle Fuzzy Numbers
6.4 Group Fuzzy TOPSIS Method
6.5 Intuitionistic Fuzzy TOPSIS Group Decision Making Method
6.6 Applications
6.7 Fuzzy DEA-TOPSIS
6.8 Conclusion
References
7 Elimination Choice Translating Reality (ELECTRE) in Uncertainty Environment
7.1 Introducing Different Versions of the ELECTRE
7.2 Electre I
7.3 Electre II
7.4 Electre III
7.5 Electre IV
7.6 ELECTRE I for Prioritizing Parks
7.7 Fuzzy ELECTRE Method
7.7.1 ELECTRE—Fuzzy Trapezoidal Form
7.7.2 Manager Selection: Employing ELECTRE Method and Fuzzy Linguistic Variables
7.8 The ELECTRE III Method and Interval-Valued Intuitionistic Fuzzy Sets
7.9 Unraveling Employee Commitment: Key Factors for Ranking and Evaluation Using the Interval-Valued Intuitionistic Fuzzy Number
7.10 Conclusion
References
8 Analytical Hierarchy Process (AHP) in Fuzzy Environment
8.1 Hierarchical Decision Structure (Threats and Opportunities)
8.2 Analytical Hierarchy Process (AHP)
8.3 Analytical Network Process (ANP)
8.4 Fuzzy AHP
8.4.1 Fuzzy AHP: First Approach
8.4.2 Fuzzy AHP: Second Approach
8.4.3 Fuzzy AHP: Third Approach
8.5 Fuzzy Analytic Network Process
8.6 Applications of Fuzzy AHP
8.7 Conclusion
References
9 VIKOR Method in Uncertainty Environment
9.1 Introduction
9.2 VIKOR
9.3 The Evaluation of Insurance Companies
9.4 Fuzzy VOKIR
9.5 Choosing a Suitable Tourism Location with Fuzzy VIKOR Method
9.6 Data Envelopment Analysis and VIKOR
9.7 Conclusion
References
10 The Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) in Uncertainty Environment
10.1 Introduction of the MACBETH method
10.2 Description of the MACBETH Method
10.2.1 Lp-Macbeth
10.3 Example of the MACBETH Method
10.4 The Fuzzy MACBETH Method: Introduction
10.5 Description of Fuzzy MACBETH Method
10.6 Applications and Example of the Fuzzy MACBETH Method
10.7 Macbeth and DEA
10.8 Conclusion
References
11 Multi Attributive Border Approximation Area Comparison (MABAC) in Uncertainty Environment
11.1 Introduction: The Power of MABAC
11.2 Description of the MABAC Method
11.3 Numerical Example of the MABAC Method
11.4 The Fuzzy MABAC Method
11.5 Applications and Example of the Fuzzy MABAC Method
11.6 Conclusion
References
12 The Complex Proportional Assessment (COPRAS) in Uncertainty Environment
12.1 Introduction
12.2 Description of the COPRAS Method
12.3 Solving Multi-Criteria Decision Making for Smart Phone Selection by COPRAS
12.4 Fuzzy COPRAS Method
12.5 Fuzzy COPRAS Approach Under Group Decision Making
12.6 Solving Investment Selection with Fuzzy COPRAS: Navigating Complex Criteria in Decision-Making
12.7 Conclusion
References
13 The Criteria Importance Through Inter-Criteria Correlation (CRITIC) in Uncertainty Environment
13.1 Introduction
13.2 CRITIC Method
13.3 Project Ranking: Evaluating and Prioritizing Projects Based on Criteria
13.4 Fuzzy CRITIC Method
13.5 Finding the Perfect Spot: Criteria for Selecting Optimal Locations for Solar Farm
13.6 Conclusion
References
14 The Multi-Objective Optimization Ratio Analysis (MOORA) in Uncertainty Environment
14.1 Introduction
14.2 The MOORA and MOOSRA Methods
14.3 Numerical Example of the MOORA Method
14.4 Fuzzy MULTIMOORA Method Using Triangular Fuzzy Number
14.5 Economic Ranking of Urban Areas Using MOORA Method: A Comprehensive Evaluation Approach
14.6 Conclusion
References