Overview
- Introduces multi-attribute decision-making methods in an imprecise environment
- Surveys and improves different approaches in dealing with MADM
- Identifies and analyzes applications in industry, management, and health
Part of the book series: Studies in Computational Intelligence (SCI, volume 1121)
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Table of contents (14 chapters)
Keywords
About this book
Authored by a leading expert in the field, this book introduces an innovative methodology that harnesses the power of fuzzy logic to enhance decision-making in multi-attribute scenarios. In a world of complexity and uncertainty, effective decision-making is paramount. Springer proudly presents a cutting-edge publication that revolutionizes decision analysis: "Fuzzy Decision Analysis: Multi-attribute Decision-Making Approach." This book stands at the forefront of decision analysis, introducing the integration of fuzzy logic into multi-attribute decision-making. It is a transformative journey into the realm of advanced decision analysis. It book not only equips you with the knowledge to comprehend the theoretical underpinnings but also empowers you to apply these insights in practical scenarios. This book serves as your indispensable companion. Its comprehensive coverage serves as a beacon, guiding you through the intricate maze of fuzzy logic and multi-attribute decision-making, ultimately empowering you to embrace innovation and master the art of making well-informed decisions in an ever-changing world.
Authors and Affiliations
Bibliographic Information
Book Title: Fuzzy Decision Analysis: Multi Attribute Decision Making Approach
Authors: Farhad Hosseinzadeh Lotfi, Tofigh Allahviranloo, Witold Pedrycz, Mohammadreza Shahriari, Hamid Sharafi, Somayeh Razipour GhalehJough
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-031-44742-6
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Hardcover ISBN: 978-3-031-44741-9Published: 24 November 2023
Softcover ISBN: 978-3-031-44744-0Due: 26 December 2023
eBook ISBN: 978-3-031-44742-6Published: 24 November 2023
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XXII, 344
Number of Illustrations: 16 b/w illustrations, 16 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Operations Research/Decision Theory