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Open AccessArticle

A MAGDM Algorithm with Multi-Granular Probabilistic Linguistic Information

by Ju-Xiang Wang 1,2
1
School of Management, Hefei University of Technology, Hefei 230009, China
2
School of Mathematics and Physics, Anhui Jianzhu University, Hefei 230601, China
Symmetry 2019, 11(2), 127; https://doi.org/10.3390/sym11020127
Received: 5 December 2018 / Revised: 15 January 2019 / Accepted: 21 January 2019 / Published: 22 January 2019
(This article belongs to the Special Issue Multi-Criteria Decision Aid methods in fuzzy decision problems)
The traditional multi-attribute group decision making (MAGDM) method needs to be improved to the integration of assessment information under multi-granular probabilistic linguistic environments. Some novel distance measures between two multi-granular probabilistic linguistic term sets (PLTSs) are proposed, and distance measures are proved to be reasonable. To calculate the weights of the alternative attributes, the extended cross-entropy method for multi-granular probabilistic linguistic term sets is proposed. Then, a novel extended MAGDM algorithm based on prospect theory (PT) is proposed. Two case studies of decision making (DM) on purchasing a car is provided to illustrate the application of the extended MAGDM algorithm. The case analyses are proposed to illustrate the novelty, feasibility, and application of the proposed MAGDM algorithm by comparing the other three algorithms based on TOPSIS, VIKOR, and Pang Qi et al.’s method. The analyses results demonstrate that the proposed algorithm based on PT is superior. View Full-Text
Keywords: decision making; distance measure; probabilistic linguistic term set; prospect theory decision making; distance measure; probabilistic linguistic term set; prospect theory
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Wang, J.-X. A MAGDM Algorithm with Multi-Granular Probabilistic Linguistic Information. Symmetry 2019, 11, 127.

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