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Hesitant fuzzy methods for multiple ...
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Zhang, Xiaolu.
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Hesitant fuzzy methods for multiple criteria decision analysis
Record Type:
Electronic resources : Monograph/item
Title/Author:
Hesitant fuzzy methods for multiple criteria decision analysis/ by Xiaolu Zhang, Zeshui Xu.
Author:
Zhang, Xiaolu.
other author:
Xu, Zeshui.
Published:
Cham :Springer International Publishing : : 2017.,
Description:
xv, 191 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:
Hesitant Fuzzy Multiple Criteria Decision Analysis Based on TOPSIS -- Hesitant Fuzzy Multiple Criteria Decision Analysis Based on TODIM -- Hesitant Fuzzy Multiple Criteria Decision Analysis Based on QUALIFLEX -- Hesitant Fuzzy Multiple Criteria Decision Analysis Based on LINMAP -- Consensus Model-Based Hesitant Fuzzy Multiple Criteria Group Decision Analysis.
Contained By:
Springer eBooks
Subject:
Operation Research/Decision Theory. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-42001-1
ISBN:
9783319420011
Hesitant fuzzy methods for multiple criteria decision analysis
Zhang, Xiaolu.
Hesitant fuzzy methods for multiple criteria decision analysis
[electronic resource] /by Xiaolu Zhang, Zeshui Xu. - Cham :Springer International Publishing :2017. - xv, 191 p. :ill. (some col.), digital ;24 cm. - Studies in fuzziness and soft computing,v.3451434-9922 ;. - Studies in fuzziness and soft computing ;v.345..
Hesitant Fuzzy Multiple Criteria Decision Analysis Based on TOPSIS -- Hesitant Fuzzy Multiple Criteria Decision Analysis Based on TODIM -- Hesitant Fuzzy Multiple Criteria Decision Analysis Based on QUALIFLEX -- Hesitant Fuzzy Multiple Criteria Decision Analysis Based on LINMAP -- Consensus Model-Based Hesitant Fuzzy Multiple Criteria Group Decision Analysis.
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.
ISBN: 9783319420011
Standard No.: 10.1007/978-3-319-42001-1doiSubjects--Topical Terms:
1620900
Operation Research/Decision Theory.
LC Class. No.: QA279.6
Dewey Class. No.: 519.542
Hesitant fuzzy methods for multiple criteria decision analysis
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Hesitant Fuzzy Multiple Criteria Decision Analysis Based on TOPSIS -- Hesitant Fuzzy Multiple Criteria Decision Analysis Based on TODIM -- Hesitant Fuzzy Multiple Criteria Decision Analysis Based on QUALIFLEX -- Hesitant Fuzzy Multiple Criteria Decision Analysis Based on LINMAP -- Consensus Model-Based Hesitant Fuzzy Multiple Criteria Group Decision Analysis.
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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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EB QA279.6
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