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Open AccessArticle

Similarity Measures of Linguistic Cubic Hesitant Variables for Multiple Attribute Group Decision-Making

by Xueping Lu * and Jun Ye
Department of Electrical and Information Engineering, Shaoxing University, 508 Huancheng West Road, Shaoxing 312000, China
*
Author to whom correspondence should be addressed.
Information 2019, 10(5), 168; https://doi.org/10.3390/info10050168
Received: 4 April 2019 / Revised: 24 April 2019 / Accepted: 24 April 2019 / Published: 5 May 2019
A linguistic cubic hesitant variable (LCHV) is a hybrid form of linguistic values in group decision-making environments. It is composed of an interval language variable and multiple single-valued language variables given by different decision-makers (DMs). Due to the uncertainty and hesitation of DMs, the numbers of language variables in different LCHVs are unequal. Thus, the least common multiple number (LCMN) extension method was adopted. Based on the included angle and distance of two LCHVs, we presented two cosine similarity measures and developed a multiple attribute group decision-making (MAGDM) approach. An example of engineer selection was used to implement the proposed LCHV MAGDM method and demonstrate the simplicity and feasibility of the proposed method. The sensitivity analysis of weight changes for the two measures showed that the similarity measure based on distance was more stable than the similarity measure based on included angle in this application. View Full-Text
Keywords: cosine measure; the least common multiple number (LCMN); linguistic cubic hesitant variable (LCHV); similarity measure; multiple attribute group decision-making cosine measure; the least common multiple number (LCMN); linguistic cubic hesitant variable (LCHV); similarity measure; multiple attribute group decision-making
MDPI and ACS Style

Lu, X.; Ye, J. Similarity Measures of Linguistic Cubic Hesitant Variables for Multiple Attribute Group Decision-Making. Information 2019, 10, 168.

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