Multiple Criteria Decision Making: Techniques, Analysis and Applications (Studies in Systems, Decision and Control, 407)

✍ Scribed by Anand J. Kulkarni (editor)

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 264
• Category: Library

✦ Synopsis

The book discusses state-of-the-art applications and methodologies of the Multiple Criteria Decision Making (MCDM) techniques and approaches. The book focuses on critical literature, underlying principles of methods and models, solution approaches, testing and validation, real-world applications, case studies, etc. The book helps evaluate strategic decision-making through advanced MCDM and integrated approaches of AI, big data, and IoT to provide realistic and robust solutions to the current problems. The book will be a guideline to the potential MCDM researchers about the choice of approaches for dealing with the complexities and modalities. The contributions of the book help readers to explore new avenues leading towards multidisciplinary research discussions. This book will be interesting for engineers, scientists, and students studying/working in the related areas.

✦ Table of Contents

Preface
Acknowledgements
Contents
Editor and Contributors
Abbreviations
Symbols
MIVES: A Multi-Attribute Value Function-Based Methodology for Sustainability Assessment
1 Introduction
2 Methodology
3 Application of MIVES in Different Sectors
3.1 MIVES in Aviation Industry
3.2 MIVES in Construction and Architecture
3.3 MIVES in Education and Teaching
3.4 MIVES in Enterprise—Case Study of Biomass Processing Enterprise
4 Conclusion
References
Base Criterion Method (BCM)
1 Introduction
2 Base Criterion Method
2.1 Strength and Direction in the Pairwise Comparisons
2.2 Steps of BCM
2.3 BCM Consistency Ratio
2.4 Examples
3 Conclusion
References
DEX (Decision EXpert): A Qualitative Hierarchical Multi-criteria Method
1 Introduction
2 DEX Method and Software: A Brief History
3 Formal Representation of a DEX Model
3.1 Attributes
3.2 Model Structure: Hierarchy of Attributes
3.3 Scales
3.4 Aggregation Functions
3.5 Alternatives
3.6 Evaluation of Alternatives
4 Dynamic Aspects of DEX
4.1 Developing Model Components and Structure
4.2 Acquiring Decision Tables and Decision Rules
4.3 Restructuring Decision Tables
4.4 Representation of Decision Tables: Complex Rules and 3D Graphics
4.5 Handling Incomplete Knowledge and Data
4.6 Analysis of Alternatives
5 Applications
5.1 One-Time Decisions
5.2 Recurring Decisions
5.3 Decision Support Systems
5.4 Other Recent Applications
6 Two Real-World Examples
6.1 Example 1: Clay Pit Location
6.2 Example 2: Electric Energy Production Technologies
7 DEX Extensions
7.1 Numeric Attributes
7.2 Weights
7.3 Combining Qualitative and Quantitative Evaluation
7.4 Handling Uncertainty Using Value Distributions
7.5 Machine Learning of DEX Models
8 Summary
References
Analysis of Fuzzy AHP and Fuzzy TOPSIS Methods for the Prioritization of the Software Requirements
1 Introduction
2 Related Work
3 An Insight into Fuzzy AHP and Fuzzy TOPSIS Methods
3.1 Fuzzy AHP
3.2 Fuzzy TOPSIS
4 Experimental Work
5 Conclusions and the Future Work
References
A Fuzzy-Based Multi-Criteria Decision-Making Approach for the Selection of Digital Image Forensic Tools
1 Introduction
2 Related Work
3 Fuzzy Set Theory
4 A Fuzzy TOPSIS Method for the Selection of Digital Image Forensic Tools
5 An Example
6 Conclusion and Future Directions
References
Why Does the Choice of Normalization Technique Matter in Decision-Making
1 Introduction
2 Normalization Methods
3 Experiments
3.1 Set with Natural Numbers
3.2 Set with Random Natural Numbers
3.3 Set with Negative Numbers
3.4 Set with Positive Values (Long Version)
3.5 Set with Positive and Negative Numbers
3.6 Set with Strongly Asymmetrical Positive Values
4 Conclusions
References
Bipolar Multicriteria Aggregation-Disaggregation Robustness Approach: Theory and Application on European e-Government Benchmarking
1 Introduction
2 Additive Value Model and UTASTAR Method
2.1 Problem Statement and Notation
2.2 The UTASTAR Ordinal Regression Method
3 The Bipolar Ordinal Regression Process of Robustness Control
3.1 Principles
3.2 Robustness Control Measures
4 Case Study: Evaluating e-Government Performance in Europe
5 Implementation—Part 1: Initialization and First Robustness Control
5.1 Initialization Phase
5.2 Creation and Ranking of the Reference Countries—Phase A
5.3 Application of UTASTAR
5.4 Evaluation of Robustness
6 Implementation—Part 2: Robust Evaluation of European e-Government
6.1 Phase B—20 Reference Countries
6.2 Phase C—25 Reference Countries
6.3 Phase D—30 Reference Countries
7 Conclusions
Appendix A: Multicriteria Evaluation of European Countries on the Eight e-Government Evaluation Criteria
Appendix B: The UTASTAR Disaggregation Algorithm
References
The COMET Method: Study Case of Swimming Training Progress
1 Introduction
2 Fuzzy Logic—Preliminaries
3 The Characteristic Objects Method
3.1 Linear Regression
4 Study Case
5 Results and Discussion
6 Conclusions
References
Brown–Gibson Model as a Multi-criteria Decision Analysis (MCDA) Method: Theoretical and Mathematical Formulations, Literature Review, and Applications
1 Introduction
2 Theoretical and Mathematical Formulations
2.1 Original Brown–Gibson Model
2.2 Buffa and Sarin Version of Brown–Gibson Model
2.3 The Extended Brown–Gibson Model
2.4 Yimen and Dagbasi Version of Brown–Gibson Model
2.5 Analytical Hierarchy Process (AHP)-Integrated Brown Gibson Model
2.6 Fuzzy Brown–Gibson Model
3 Litterature Review
4 Application: Original Brown–Gibson Model for a Commercial Centre Location Decision
5 Conclusions
References
A Grey Approach for the Computation of Interactions Between Two Groups of Irrelevant Variables of Decision Matrices
1 Introduction
2 Grey Numbers and Operations
3 Methods and Tools
3.1 Strategies Interaction Model (SIM)
3.2 Shannon’s Entropy
3.3 Grey TOPSIS
4 Proposed Methodology
5 Method Application and Results
5.1 Selection of Strategies SIM
5.2 Evaluation of Criteria: Prioritization of Criteria Due to the Selected Strategies
5.3 Supplier Selection
6 Comparison
7 Conclusion
References
Statistical Analysis of KMM Program—An Educational Intervention
1 Introduction
2 Background and Related Work
2.1 Educational Intervention
2.2 Intervention Evaluation
3 Methodology
3.1 Method
3.2 Evaluation Framework
3.3 Questionnaire Validation
4 Analysis, Result, and Discussion
4.1 Cronbach Alpha Test
4.2 Descriptive Statistics to Study Impact of KMM Program
4.3 Correlational Analysis
4.4 Factor Analysis
4.5 Impact Analysis of KMM Program
4.6 Discussion
4.7 Practical Implication
5 Conclusion and Future Scope
References