Xiaobing Mao, Hao Wu, Shuping Wan*
CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1751-1792, 2022, DOI:10.32604/cmes.2022.019501
- 19 April 2022
Abstract This paper proposes a personalized comprehensive cloud-based method for heterogeneous multi-attribute group
decision-making (MAGDM), in which the evaluations of alternatives on attributes are represented by LTs (linguistic
terms), PLTSs (probabilistic linguistic term sets) and LHFSs (linguistic hesitant fuzzy sets). As an effective tool
to describe LTs, cloud model is used to quantify the qualitative evaluations. Firstly, the regulation parameters of
entropy and hyper entropy are defined, and they are further incorporated into the transformation process from LTs
to clouds for reflecting the different personalities of decision-makers (DMs). To tackle the evaluation information
in the form… More >
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