Hesitant Fuzzy Methods for Multiple Criteria Decision Analysis

ISBN-13: 9783319420004 / Angielski / Twarda / 2016 / 191 str.

Xiaolu Zhang; Zeshui Xu

Opis

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.

Recenzje

"This book mainly investigates the multiple criteria decision making (MCDM) or multiple criteria group decision making (MCGDM) problems in which the criteria values and/or the weights of criteria are expressed as hesitant fuzzy elements (HFEs). ... The book is beautifully written. It can be used as a reference for researchers and practitioners working in the field of fuzzy mathematics, operations research, information science, management science and engineering, etc. and as a textbook for postgraduate and senior undergraduate students." (I. M. Stancu-Minasian, zbMATH 1356.90008, 2017)

Spis treści

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.

Blurb

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.