A handbook on multi-attribute decision-making methods

A handbook on multi-attribute decision-making methods /

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Bibliographic Details
Main Authors: Bozorg-Haddad, Omid, 1974- (Author), Zolghadr-Asli, Babak (Author), Loaiciga, Hugo A. (Author)
Corporate Author: ProQuest (Firm)
Format: Electronic eBook
Language:English
Published: Hoboken, NJ : Wiley, [2021]
Series:Wiley series in operations research and management science
Subjects:
Multiple criteria decision making.
Online Access:Connect to this title online (unlimited simultaneous users allowed; 325 uses per year)
Table of Contents:
  • Machine generated contents note: 1. Overview of the Art of Decision-making
  • 1.1. Introduction
  • 1.2. Classification of MADM Methods
  • 1.2.1. Preference Evaluation Mechanism
  • 1.2.2. Attributes' Interactions
  • 1.2.3. Mathematical Nature of Attributes' Values
  • 1.2.3.1. Deterministic Vs. Nondeterministic
  • 1.2.3.2. Fuzzy Vs. Crisp
  • 1.2.4. Number of Involved Decision-makers
  • 1.3. Brief Chronicle of MADM Methods
  • 1.4. Conclusion
  • References
  • 2. Simple Weighting Methods: Weighted Sum and Weighted Product Methods
  • 2.1. Introduction
  • 2.2. Weighted Sum Method
  • 2.2.1. Step 1: Defining the Decision-making Problem
  • 2.2.2. Step 2: Normalizing the Elements of the Decision-matrix
  • 2.2.3. Step 3: Aggregating the Preference of Alternatives
  • 2.3. Weighted Product Method
  • 2.4. Conclusion
  • References
  • 3. Analytic Hierarchy Process (AHP)
  • 3.1. Introduction
  • 3.2. Hierarchical Structure
  • 3.3. Pairwise Comparison
  • 3.4. Inconsistency
  • 3.5. Quadruple Axioms of the AHP
  • 3.6. Stepwise Description of the AHP Method
  • 3.6.1. Step 1: Defining the Decision-making Problem
  • 3.6.2. Step 2: Performing the Pairwise Comparison Through the Hierarchical Structure
  • 3.6.3. Step 3: Estimating the Preference Value Vectors
  • 3.6.4. Step 4: Synthesizing and Computing the Overall Preference Value of Alternatives
  • 3.6.5. Step 5: Evaluating the Results' Rationality and Selecting the Best Alternative
  • 3.7. Conclusion
  • References
  • 4. Analytic Network Process (ANP)
  • 4.1. Introduction
  • 4.2. Network Vs. Hierarchy Structure
  • 4.3. Stepwise Instruction to the ANP Method
  • 4.3.1. Step 1: Defining the Decision-making Problem
  • 4.3.2. Step 2: Conducting a Pairwise Comparison of the Elements of the Decision-making Problem
  • 4.3.3. Step 3: Forming the Supermatrix
  • 4.3.4. Step 4: Computing the Weighted Supermatrix
  • 4.3.5. Step 5: Computing the Global Priority Vectors and Choosing the Most Suitable Alternative
  • 4.4. Conclusion
  • References
  • 5. Best-Worst Method (BWM)
  • 5.1. Introduction
  • 5.2. Basic Principles of the BWM
  • 5.3. Stepwise Description of the BWM
  • 5.3.1. Step 1: Defining the Decision-Making Problem
  • 5.3.2. Step 2: Determining the Reference Criteria
  • 5.3.3. Step 3: Pairwise Comparisons
  • 5.3.4. Step 4: Computing the Optimal Weights
  • 5.3.5. Step 5: Measuring the Inconsistency of Decision-Makers Judgments
  • 5.4. Conclusion
  • References
  • 6. TOPSIS
  • 6.1. Introduction
  • 6.2. Stepwise Description of the TOPSIS Method
  • 6.2.1. Step 1: Establishing the Formation of the Decision-making Problem
  • 6.2.2. Step 2: Normalizing the Element of the Decision-matrix
  • 6.2.3. Step 3: Computing the Weighted Normalized Preference Values
  • 6.2.4. Step 4: Defining the Reference Alternatives
  • 6.2.5. Step 5: Calculation of the Separation Measure
  • 6.2.6. Step 6: Computing the Relative Closeness to the Ideal Solution
  • 6.2.7. Step 7: Ranking the Alternatives
  • 6.3. Common Misinterpretation of TOPSIS Results
  • 6.4. Conclusion
  • References
  • 7. VIKOR
  • 7.1. Introduction
  • 7.2. Stepwise Description of the VIKOR Method
  • 7.2.1. Step 1: Modeling the Decision-Making Problem
  • 7.2.2. Step 2: Normalizing the Element of the Decision-Matrix
  • 7.2.3. Step 3: Compute the "Group Satisfaction" and "Individual Regret" Parameters
  • 7.2.4. Step 4: Computing the VIKOR Parameter
  • 7.2.5. Step 5: Ranking the Alternatives
  • 7.2.6. Step 6: Determining the Compromise Solution
  • 7.3. Conclusion
  • References
  • 8. ELECTRE
  • 8.1. Introduction
  • 8.2. Brief History of the ELECTRE Family of Methods
  • 8.3. ELECTRE I
  • 8.4. ELECTRE II
  • 8.5. ELECTRE III
  • 8.6. ELECTRE IV
  • 8.7. Conclusion
  • References
  • 9. PROMETHEE
  • 9.1. Introduction
  • 9.2. Common Ground of the PROMETHEE Family
  • 9.2.1. Stage 1: Construction of the Generalized Criteria
  • 9.2.2. Stage 2: Mapping the Outrank Relation on the Set of Feasible Alternatives
  • 9.2.3. Stage 3: Evaluation the Relation Among the Feasible Alternatives
  • 9.3. PROMETHEE I
  • 9.4. PROMETHEE II
  • 9.5. PROMETHEE III
  • 9.6. PROMETHEE IV
  • 9.7. Conclusion
  • References
  • 10. Superiority and Inferiority Ranking (SIR)
  • 10.1. Introduction
  • 10.2. Foundational Bases of the SIR Method
  • 10.3. Stepwise Description of the SIR Method
  • 10.3.1. Step 1: Establishing the Formation of the Decision-Making Problem
  • 10.3.2. Step 2: Computing the Superiority and Inferiority Scores
  • 10.3.3. Step 3: Forming the Superiority and Inferiority Matrices
  • 10.3.4. Step 4: Superiority and Inferiority Flows
  • 10.3.5. Step 5: Ranking the Set of Feasible Alternatives
  • 10.4. Conclusion
  • References
  • 11. PAPRIKA
  • 11.1. Introduction
  • 11.2. Stepwise Description of PAPRIKA
  • 11.2.1. Step 1: Defining the Decision-Making Problem
  • 11.2.2. Step 2: Identifying the Nondominated Pairs of Alternative
  • 11.2.3. Step 3: Ranking the Pairs of Nondominated Solutions
  • 11.2.4. Step 4: Calculating the Complete Ranking of Alternatives
  • 11.3. Conclusion
  • References
  • 12. Gray Relational Analysis
  • 12.1. Introduction
  • 12.2. Gray System Theory: The Foundation and Basic Principles
  • 12.3. Gray Relational Modeling
  • 12.4. Gray Theory in Relation to MADM
  • 12.5. Conclusion
  • References
  • A. Weight Assignment Approaches
  • A.1. Subjective Approach: Weighted Least Squares
  • A.2. Objective Approach: Multiobjective Programming Model
  • References
  • B. Benchmark Example and a Comparison between Objective- and Subjective-Based MADM Methods
  • References.

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