
- 85 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
About this book
Multiple attribute decision making (MADM) procedures, a process for making preference decisions over the available alternatives which are characterized by multiple (usually conflicting) attributes are useful for improving decision making in a wide range of circumstances--from professional to managerial to political. Using real-world case examples, the authors introduce the reader to normative (for optimal decisions) MADM models. Beginning in chapter 2 with and introductions to the various attributes in a decision, the authors explore how MADM methods can be used for descriptive purposes to model the existing decision-making process, noncompensatory and scoring methods, accommodation of soft data, construction of a multiple decision support system, and the validity of methods. The authors also include a presentation of the advanced procedures of TOPSIS and ELECTRE. This manual offers social scientists an encapsulated view of MADM methods, their characteristics, applicability, and the methods for solving MADM problems.
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access Multiple Attribute Decision Making by K. Paul Yoon,Ching-Lai Hwang in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Cover
- Contents
- Series Editor's Introduction
- Acknowledgments
- Chapter 1 - Introduction
- 1.1. Multiple Attribute Decision Making
- 1.2. Budget Reduction Decision: A MADM Case
- 1.3. Ben Franklin's Solution: Classic MADM Approach
- 1.4. Classification of MADM Methods
- 1.5. Scope of the Monograph
- Chapter 2 - Attribute Generation, Data, and Weight
- 2.1. Attribute Generation
- 2.2. Attribute weighting
- 2.2.1. Weights from Ranks
- 2.2.2. Ratio Weighting
- 2.3. Quantification of Qualitative Ratings
- 2.4. Normalization of Attribute Ratings
- Chapter 3 - Noncompensatory Methods
- 3.1. Dominance
- 3.2. Satisficing Methods
- 3.2.1. Conjunctive Method
- 3.2.2. Disjunctive Method
- 3.3. Sequential Elimination Methods
- 3.3.1. Lexicographic Methods
- 3.3.2. Elimination by Aspects
- 3.4. Attitude Oriented Methods
- 3.4.1. Maximin
- 3.4.2. Maximax
- Chapter 4 - Scoring Methods
- 4.1. Simple Additive Weighting (SAW) Method
- 4.2. Weighted Product Method
- Chapter 5 - Topsis
- 5.1. Positive-Ideal and Negative-Ideal Solutions
- 5.2. Topsis
- Chapter 6 - Electre
- 6.1. Outranking Relationships
- 6.2. Preferred Alternatives
- 6.3. Electre
- 6.4. Complementary Analysis
- Chapter 7 - Methods for Qualitative Data
- 7.1. Median Ranking Method
- 7.2. AHP: Hierarchical SAW Method
- Chapter 8 - Extensions
- 8.1. Soft Data Implementation
- 8.2. Decision Support System for MADM
- 8.3. Choice and Validity of Methods
- References
- About the Authors