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author:

Wang, Ying-Ming (Wang, Ying-Ming.) [1] | Parkan, Celik (Parkan, Celik.) [2]

Indexed by:

EI

Abstract:

The aggregation of fuzzy opinions is an important component of group decision analysis with fuzzy information. This paper proposes two new approaches for the assessment of the weights to be associated with fuzzy opinions. These approaches involve, respectively, the minimization of the sum of squared distances from one weighted fuzzy opinion to another, which is called the least squares distance method (LSDM), and the minimization of the sum of squared differences between the defuzzified values of any two weighted fuzzy opinions, which is called the defuzzification-based least squares method (DLSM). The two approaches are developed and numerical examples are presented to illustrate their simplicity and effectiveness in aggregating fuzzy opinions. © 2006 Elsevier Inc. All rights reserved.

Keyword:

Decision theory Distance measurement Fuzzy sets Least squares approximations Numerical methods Weighing

Community:

  • [ 1 ] [Wang, Ying-Ming]School of Public Administration, Fuzhou University, Fuzhou, 350002, China
  • [ 2 ] [Wang, Ying-Ming]Center for Accounting Studies, Xiamen University, Xiamen, Fujian 361005, China
  • [ 3 ] [Parkan, Celik]Department of Management, Long Island University, C.W. Post Campus, 720 Northern Blvd, Brookville, NY 11548, United States

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Source :

Information Sciences

ISSN: 0020-0255

Year: 2006

Issue: 23

Volume: 176

Page: 3538-3555

1 . 0 0 3

JCR@2006

0 . 0 0 0

JCR@2023

JCR Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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