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Novel Multiple Attribute Group Decision-Making Methods Based on Linguistic Intuitionistic Fuzzy Information
Article

A Probabilistic Linguistic Multiple Attribute Decision Making Based on a New Correlation Coefficient Method and its Application in Hospital Assessment

by 1, 1,2,3,* and 2
1
School of Business, Ningbo University, Ningbo 315211, China
2
College of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, China
3
School of Management, Fudan University, Shanghai 200433, China
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(3), 340; https://doi.org/10.3390/math8030340
Received: 2 February 2020 / Revised: 27 February 2020 / Accepted: 28 February 2020 / Published: 4 March 2020
(This article belongs to the Special Issue Group Decision Making Based on Artificial Intelligence)
The probabilistic linguistic term set (PLTS) is a newly emerging mathematical tool for handling uncertainties. It is considered a useful extension of linguistic term sets associated with probability information and can improve the effectiveness of multiple attribute decision making (MADM). This paper proposes a new PLTS correlation coefficient and addresses its usefulness in MADM problems. For achieving this aim, some new concepts of mean, variance, and covariance of the PLTS are first proposed. Moreover, a novel PLTS Pearson correlation coefficient is defined to overcome the shortcomings of the existing methods, whose significant feature is that it lies in the interval [−1,1], which makes it more effective in reflecting the negative and positive correlation between PLTSs. A weighted PLTS Pearson correlation coefficient is further defined to consider the importance of attribute weights and expand the scope of application. Then, a relative PLTS closeness coefficient is constructed based on the developed Pearson correlation coefficient, and based on which, a Pearson correlation-based TOPSIS (technique for order of preference by similarity to ideal solution) approach for MADM problems is developed. Finally, the effectiveness as well as the applicability of the developed method are illustrated through numerical examples and comparative analysis. View Full-Text
Keywords: probabilistic linguistic term set; TOPSIS; Pearson correlation coefficient; multiple attribute decision making; hospital assessment probabilistic linguistic term set; TOPSIS; Pearson correlation coefficient; multiple attribute decision making; hospital assessment
MDPI and ACS Style

Luo, D.; Zeng, S.; Chen, J. A Probabilistic Linguistic Multiple Attribute Decision Making Based on a New Correlation Coefficient Method and its Application in Hospital Assessment. Mathematics 2020, 8, 340. https://doi.org/10.3390/math8030340

AMA Style

Luo D, Zeng S, Chen J. A Probabilistic Linguistic Multiple Attribute Decision Making Based on a New Correlation Coefficient Method and its Application in Hospital Assessment. Mathematics. 2020; 8(3):340. https://doi.org/10.3390/math8030340

Chicago/Turabian Style

Luo, Dandan, Shouzhen Zeng, and Ji Chen. 2020. "A Probabilistic Linguistic Multiple Attribute Decision Making Based on a New Correlation Coefficient Method and its Application in Hospital Assessment" Mathematics 8, no. 3: 340. https://doi.org/10.3390/math8030340

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