This book is designed and developed to link the theory, emerging methods, and applications. The theory part focuses on explaining the background and concept of multi-attribute decision-making. The emerging methods part elaborates on frequently adopted and emerging approaches in multi-attribute decision-making. The applicatoins part provides in-depth illustrations of various methods using numerical examples.
• Uses uncertainty theories such as fuzzy sets, Fermatean sets and Dempster-Shafer model.
• Illustrates MADM techniques such as AHP, TOPSIS, MOORA, CoCoSO, GRA, BWM, DEA etc. and its hybridization with uncertainty theories.
• Covers practical applications from diverse fields, including production engineering, industrial engineering, mechanical engineering, and civil engineering.
• Explains circular economy, industry 4.0, supplier selection, process parameter optimization, building sustainability, sustainable manufacturing etc.
The book is primarily written for graduate students and academic researchers in the fields of mechanical engineering, engineering mathematics, mathematics, engineering design, production engineering, manufacturing engineering, and industrial engineering.
Table of Contents:
Chapter 1. Evaluating Relative Efficiencies of Government Schools in Delhi Region through Data Envelopment Analysis. Chapter 2. Optimizing location, allocation, inventory, and transportation in a circular economy network using a multi-objective mathematical model. Chapter 3. Grey theory based Ranking framework Towards Successful Industry 4.0 Implementation. Chapter 4. Application of Fuzzy AHP and Fuzzy TOPSIS for establishing priority weight of multiple criteria for building sustainability assessment. Chapter 5. Application of Emerging Uncertainty Theories in MADM/MCDM Problems: A Review. Chapter 6. Practical Application of Multi-Attribute Decision-Making in the Oil and Gas Industry. Chapter 7. Deriving Criteria Weights for the Analytical Framework for Grading and Listing Heritage Buildings: Comparative Analysis of AHP and Fuzzy AHP. Chapter 8. Ranking of cricket teams using Multi-Attribute Decision Making approach: BHARAT. Chapter 9. Multi-Objective Optimization for Turning using MOORA & Novel CoCoSO Approach. Chapter 10. A Hybrid MADM Approach Integrating Fuzzy Logic and MOORA. Chapter 11. Optimization of Process Parameters for FSP Surface Modified Al6061reinforced with nano TiAl sheets using TOPSIS Multi-Criteria Decision-Making (MCDM) Technique. Chapter 12. Multi-attribute optimisation of PMEDM process parameters for machining Ti6Al7Nb–a biocompatible alloy. Chapter 13. Integrated Approach for Resilient Supplier Selection: Application of DD-GDA-GT-EMSS Framework. Chapter 14. Dynamic Fermatean Fuzzy Set: Modelling Dynamic Multicriteria Decisions. Chapter 15. Assessment of India’s High Ethanol Blending Future using A Fuzzy-AHP and Dempster-Shafer-Based Decision Model. Chapter 16. GRA, TOPSIS, and DFA-Aided Decision-Making in Concrete Technology Chapter 17. Analyzing sustainable manufacturing barriers to improve its adoption: a robust best worst method approach.
About the Author :
Rajesh S. Prabhu Gaonkar is presently working as a Professor on Deputation at the School of Mechanical Sciences, Indian Institute of Technology Goa, India. He has published over 75 research papers in various National and International Conferences and Journals; co-authored a book on “Fuzzy Reliability -- Concepts and Applications” (2007) and co-authored a monograph “Six-Sigma: A Key to Enterprise Excellence” (2008). His teaching areas include industrial engineering, operations research, advanced optimization, reliability engineering/ reliability-based design, maintenance engineering and management, operations management, system modeling, and simulation. His research areas include fuzzy set applications in reliability, maintenance engineering, and multi-attribute decision-making.
