Score function based on concentration degree for probabilistic linguistic term sets: An application to TOPSIS and VIKOR

2020 ◽  
Author(s):  
Mingwei Lin ◽  
Zheyu Chen ◽  
Zeshui Xu ◽  
Xunjie Gou ◽  
Francisco Herrera
Keyword(s):  
Score Function ◽  
Linguistic Term ◽  
Probabilistic Linguistic Term Sets ◽  
Concentration Degree

scholarly journals The application of probabilistic linguistic CODAS method based on new score function in multi-criteria decision-making

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Liuxin Chen ◽  
Xiaoling Gou
Keyword(s):  
Decision Making ◽  
Score Function ◽  
Multi Criteria Decision Making ◽  
Topsis Method ◽  
Linguistic Terms ◽  
Complete Representation ◽  
Linguistic Term ◽  
Probabilistic Linguistic Term Sets ◽  
Todim Method

AbstractProbabilistic linguistic term sets (PLTSs) play an important role in multi-criteria decision-making(MCDM) problems because it can not only describe objects with several possible linguistic terms, but also represent the proportion of each linguistic term, which can effectively avoid the distortion of decision information to a greater extent and ensure the credibility of decision results. First, to compare PLTS more simply and reasonably, we define a new score function that takes into account partial deviations. Then considering the superiority of the classic combinative distance-based assessment (CODAS) method in the complete representation of information, it is extended to the probabilistic linguistic environment. Subsequently, we improved the classic CODAS method and proposed the PL-CODAS method. Finally, we apply the PL-CODAS method to a cases of venture investors choosing emerging companies, and we compare the proposed method with PL-TOPSIS method, PL-TODIM method and PL-MABAC method to verify its applicability and effectiveness.

scholarly journals A Novel IVPLTS Decision Method Based on Regret Theory and Cobweb Area Model

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Peng Li ◽  
Huanhuan Peng
Keyword(s):  
Multiple Criteria Decision Making ◽  
Score Function ◽  
Decision Makers ◽  
Regret Theory ◽  
Area Model ◽  
Decision Method ◽  
Linguistic Term ◽  
Probabilistic Linguistic Term Sets ◽  
Novel Method ◽  
Interval Valued

For the multiple criteria decision-making (MCDM) problem with interval-valued probabilistic linguistic information, we propose a novel method considering the regret theory and cobweb area model. We first propose a new score function, which can be used to compare different interval-valued probabilistic linguistic term sets (IVPLTSs) and transform the IVPLTSs into crisp numbers. Some properties of the score function are verified. Then, we utilize the regret theory to obtain the perceived utilities of decision makers (DMs), which can reflect the DMs’ bounded rationality. Furthermore, we use the cobweb area model to aggregate decision information. Finally, a real case of evaluating nursing homes is used to illustrate the effectiveness and features of our method.

Operators and comparisons of probabilistic linguistic term sets

2019 ◽  
Vol 34 (7) ◽  
pp. 1476-1504 ◽  
Author(s):  
Wangwang Yu ◽  
Hui Zhang ◽  
Boquan Li
Keyword(s):  
Linguistic Term ◽  
Probabilistic Linguistic Term Sets

Transforming and decision-making based on probabilistic linguistic term sets with comparative linguistic expressions and incomplete assessments

2021 ◽  
Vol 40 (1) ◽  
pp. 491-506
Author(s):  
Ao Shen ◽  
Shuling Peng ◽  
Gaofei Liu
Keyword(s):  
Decision Making ◽  
Probability Distribution ◽  
Common Sense ◽  
Linguistic Term ◽  
Probabilistic Linguistic Term Sets ◽  
Probability Information ◽  
Incomplete Assessments

The probabilistic linguistic term sets (PLTSs) are widely used in decision-making, due to its convenience of evaluation, and allowances of probability information. However, there are still some cases where it is not convenient to give an evaluation using the PLTS gramma. Sometimes the evaluators can only give a comparative relationship between alternatives, sometimes evaluators may have difficulty understanding all the alternatives and cannot give a complete assessment. Therefore, we propose a method to transform the comparative linguistic expressions (CLEs) into PLTSs, and the comparison objects of CLEs are alternatives evaluated by PLTSs. And the probability distribution has been adjusted to make the transformation more in line with common sense. Then, a method to correct the deviation is proposed, allowing alternatives to be compared in the case of incomplete assessment. Combining the above two methods, we propose a decision-making method when both CLEs and incomplete assessments coexist. With the study in this paper, the limitations of PLTS-based evaluation and decision-making are reduced and the flexibility of using PLTS is improved.

scholarly journals Hesitant fuzzy linguistic two-sided matching decision making

Filomat ◽  
2018 ◽  
Vol 32 (5) ◽  
pp. 1853-1860 ◽  
Author(s):  
Qi Yue ◽  
Bingwen Yu ◽  
Yongshan Peng ◽  
Lei Zhang ◽  
Yu Hong
Keyword(s):  
Decision Making ◽  
Score Function ◽  
Ahp Method ◽  
Goal Model ◽  
Sensitive Analysis ◽  
Linguistic Term ◽  
Fuzzy Linguistic ◽  
Weighting Technique

This paper combines the theory of hesitant fuzzy linguistic term sets (HFLTSs) with two-sided matching decision making (TSMDM). The related definitions of HFLTSs and two-sided matchings (TSMs) are introduced. Then, the problem of TSMDM with HFLTSs is presented. For solving this problem, a model of TSMDM with HFLTSs is developed. The AHP method is used to determine the important degrees of agents of each side. On this base, the model of TSMDM can be changed into a double-goal model with HFLTSs. Then, the double-goal model with HFLTSs is changed into the double-goal model with scores through using the proposed score function. Furthermore, the double-goal model can be changed into a single-goal model by using the linear weighting technique once again. The scheme of TSM can be obtained through solving the single-goal model. At last, an example with sensitive analysis is provided for the illustration of the presented approach of TSM.

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