Hesitant Fuzzy Methods for Multiple Criteria Decision Analysis

Business & Finance, Management & Leadership, Operations Research, Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Hesitant Fuzzy Methods for Multiple Criteria Decision Analysis by Xiaolu Zhang, Zeshui Xu, Springer International Publishing
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Author: Xiaolu Zhang, Zeshui Xu ISBN: 9783319420011
Publisher: Springer International Publishing Publication: October 8, 2016
Imprint: Springer Language: English
Author: Xiaolu Zhang, Zeshui Xu
ISBN: 9783319420011
Publisher: Springer International Publishing
Publication: October 8, 2016
Imprint: Springer
Language: English

The book offers a comprehensive introduction to methods for solving multiple criteria decision making and group decision making problems with hesitant fuzzy information. It reports on the authors’ latest research, as well as on others’ research, providing readers with a complete set of decision making tools, such as hesitant fuzzy TOPSIS, hesitant fuzzy TODIM, hesitant fuzzy LINMAP, hesitant fuzzy QUALIFEX, and the deviation modeling approach with heterogeneous fuzzy information. The main focus is on decision making problems in which the criteria values and/or the weights of criteria are not expressed in crisp numbers but are more suitable to be denoted as hesitant fuzzy elements. The largest part of the book is devoted to new methods recently developed by the authors to solve decision making problems in situations where the available information is vague or hesitant. These methods are presented in detail, together with their application to different type of decision-making problems. All in all, the book represents a valuable reference guide for graduate students and researchers in the both fields of fuzzy logic and decision making. 

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The book offers a comprehensive introduction to methods for solving multiple criteria decision making and group decision making problems with hesitant fuzzy information. It reports on the authors’ latest research, as well as on others’ research, providing readers with a complete set of decision making tools, such as hesitant fuzzy TOPSIS, hesitant fuzzy TODIM, hesitant fuzzy LINMAP, hesitant fuzzy QUALIFEX, and the deviation modeling approach with heterogeneous fuzzy information. The main focus is on decision making problems in which the criteria values and/or the weights of criteria are not expressed in crisp numbers but are more suitable to be denoted as hesitant fuzzy elements. The largest part of the book is devoted to new methods recently developed by the authors to solve decision making problems in situations where the available information is vague or hesitant. These methods are presented in detail, together with their application to different type of decision-making problems. All in all, the book represents a valuable reference guide for graduate students and researchers in the both fields of fuzzy logic and decision making. 

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