On the fusion of multi-granularity linguistic label sets in group decision making

Authors:
Zhifeng Chen;David Ben-Arieh
Affiliations:
Department of Industrial and Manufacturing Systems Engineering, Kansas State University, Manhattan, KS 66506, USA;Department of Industrial and Manufacturing Systems Engineering, Kansas State University, Manhattan, KS 66506, USA
Venue:
Computers and Industrial Engineering
Year:
2006

Citing 16
Cited 18

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Abstract

Group decision-making problem is a common and crucial human activity. Many times due to inherent uncertainty, exact numbers can be either costly or unnecessary to be applied to express experts' opinions or preferences. The use of linguistic labels makes expert judgment more reliable and informative for decision-making. This paper presents a new fusion approach for multi-granularity linguistic information for managing information assessed in different linguistic term sets (multi-granularity linguistic term sets). The paper also presents the application of this approach to a decision-making problem with multiple information sources, assuming that the linguistic performance values given to the alternatives by the different experts are represented in linguistic term sets with different granularity and/or semantic.