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Multi-Attribute Decision-Making: Bridging Theory and Practice / by Ashok Kumar Yadav, Ali Ahmadian, Ajay Pratap.

Springer eBooks EBA - Intelligent Technologies and Robotics Collection 2026 Available online

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Format:
Book
Author/Creator:
Yadav, Ashok Kumar.
Series:
Transactions on Computer Systems and Networks, 2730-7492
Language:
English
Subjects (All):
Computational intelligence.
Artificial intelligence.
Operations research.
Computational Intelligence.
Artificial Intelligence.
Operations Research and Decision Theory.
Local Subjects:
Computational Intelligence.
Artificial Intelligence.
Operations Research and Decision Theory.
Physical Description:
1 online resource (0 pages)
Edition:
1st ed. 2026.
Place of Publication:
Singapore : Springer Nature Singapore : Imprint: Springer, 2026.
Summary:
This book offers a comprehensive, mathematically grounded introduction to multi-attribute decision-making (MADM) for undergraduate, graduate, and doctoral students, as well as researchers in engineering, management, economics, and biology. It bridges theory and practice, covering fundamental concepts, advanced methods, and MATLAB implementations. Topics include critical, subjective, objective, and comprehensive weighting methods, ranking techniques, and their integration for solving complex decision problems. The book addresses challenges such as ranking abnormalities, complexity, and applicability in emerging applications. It also explores fuzzy MADM for handling uncertainty and non-sharp boundaries, highlighting recent research directions and open challenges. Filling a gap in the literature, this book serves as a valuable resource for academics and professionals seeking to apply MADM in dynamic, interdisciplinary contexts.
Contents:
Chapter 1. Introduction to Decision Theory
Chapter 2. Normalization Strategies
Chapter 3. Subjective Weigh Methods
Chapter 4. Objective Weight Methods
Chapter 5. Integrated Weight Methods
Chapter 6. Multi-Attribute Decision-Making Models
Chapter 7. Challenges in MADM Models
Chapter 8. Applications of MADM.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
981-9547-82-2
9789819547821
OCLC:
1572213123

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