Hesitant Fuzzy Methods for Multiple Criteria Decision Analysis (Studies in Fuzziness and Soft Computing, 345)

Zhang, Xiaolu; Xu, Zeshui

ISBN 10: 3319824767 ISBN 13: 9783319824765

Editorial: Springer, 2018

Idioma: Ingl�s

Condici�n: Nuevo Encuadernaci�n de tapa blanda

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Detalles bibliogr�ficos

T�tulo

Hesitant Fuzzy Methods for Multiple Criteria Decision Analysis (Studies in Fuzziness and Soft Computing, 345)

Editor

Springer

Fecha de publicaci�n

2018

Idioma

Ingl�s

ISBN 10

3319824767

ISBN 13

9783319824765

Encuadernaci�n

Encuadernaci�n de tapa blanda

Estado

New

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Sinopsis

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.

De la contraportada

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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