Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/29036
Title: Multi-attribute group decision-making with multi-granularity linguistic assessment information : an improved approach based on deviation and TOPSIS
Authors: Liu, S
Chan, FTS 
Ran, W
Keywords: Multi-attribute group decision-making
Multi-granularity
Standard and mean deviation
TOPSIS
Issue Date: 2013
Publisher: Elsevier Science Inc
Source: Applied mathematical modelling, 2013, v. 37, no. 24, p. 10129-10140 How to cite?
Journal: Applied Mathematical Modelling 
Abstract: With respect to group decision-making problems with multi-granularity linguistic assessment information, a new approach is proposed. Firstly, the computational formulae are given in order to transform and unify the multi-granularity linguistic comparison matrices. Secondly, the method of standard and mean deviation is applied to determine the unknown attribute weights, and the weights of the decision makers will be determined by using the extended TOPSIS (technique for order preference by similarity to an ideal solution) method. Finally, based on the LWAA (linguistic weighted arithmetic averaging) operator, information on the preference provided by each decision maker is aggregated into the comprehensive evaluation value of each alternative, and the most desirable alternative is selected. The proposed approach expands the research in multi-attribute group decision-making with multi-granularity linguistic assessment information by both considering the weights of the attributes and decision makers, and objective weighting for them. A numerical example is given to illustrate the practicability and usefulness of the proposed approach.
URI: http://hdl.handle.net/10397/29036
ISSN: 0307-904X
DOI: 10.1016/j.apm.2013.05.051
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