Linguistic hesitant intuitionistic fuzzy decision-making method based on VIKOR

TODIM-VIKOR method based on hybrid weighted distance under probabilistic uncertain linguistic information and its application in medical logistics center site selection

At a time of global epidemic control, the location of the medical logistics distribution center (MLDC) has an important impact on the operation of the entire logistics system to reduce the operating costs of the company, enhance the service quality and effectively control the COVID-19 on the premise of increasing the company's profits. Thus, the research on the location of MLDC has important theoretical and practical application significance separately. Recently, the TODIM and VIKOR method has been used to solve multiple-attribute group decision-making (MAGDM) issues. The probabilistic uncertain linguistic term sets (PULTSs) are used as a tool for characterizing uncertain information. In this paper, we design the TODIM-VIKOR model to solve the MAGDM in PULT condition. Firstly, some basic concept of PULTSs is reviewed, and TODIM and VIKOR method are introduced. The extended TODIM-VIKOR model is proposed to tackle MAGDM problems under the PULTSs. At last, a numerical case study for medical logistics center site selection (MLCSS) is given to validate the proposed method.

Research on teaching quality evaluation of Chinese medicine specialty in higher vocational colleges with probabilistic uncertain linguistic TODIM-VIKOR method

Traditional Chinese medicine is a complex discipline that needs to combine theory with practice under the background of the magnificent Chinese history and civilization. It is a subject that needs “lifelong” learning. Teachers should gradually change the dull and rigid teaching mode in the past and explore a scientific and effective teaching mode that conforms to the background of the current era. Applying the advantages of the Internet to organically integrate teaching modes such as flipped classroom, which can stimulate students’ learning interest, cultivate students’ thinking mode of traditional Chinese medicine and clinical problem-solving ability, and realize the common development of students’ ability and quality of traditional Chinese medicine. While improving the teaching effect of internal medicine of traditional Chinese medicine, this diversified teaching method will provide new ideas and methods for deepening the reform of traditional Chinese medicine teaching and lead the teaching of traditional Chinese medicine to a new level. The teaching quality evaluation of Chinese medicine specialty in higher vocational colleges is classical multiple-attribute group decision-making (MAGDM) issues. Recently, the TODIM and VIKOR method has been used to solve MAGDM issues. The probabilistic uncertain linguistic term sets (PULTSs) are used as a tool for characterizing uncertain information during the teaching quality evaluation of Chinese medicine specialty in higher vocational colleges. In this manuscript, we design the TODIM-VIKOR model to solve the MAGDM under PULTSs. In the end, a numerical case study for teaching quality evaluation of Chinese medicine specialty in higher vocational colleges is given to validate the proposed method.

VIKOR Method for MAGDM Based on Q-Rung Interval-Valued Orthopair Fuzzy Information and Its Application to Supplier Selection of Medical Consumption Products

The VIKOR model has been considered a viable tool for many decision-making applications in the past few years, given the advantages of considering the compromise between maximizing the utility of group and minimizing personal regrets. The q-rung interval-valued orthopair fuzzy set (q-RIVOFS) is a generalization of intuitionistic fuzzy set (IFS) and Pythagorean fuzzy set (PFS) and has emerged to solve more complex and uncertain decision making problems which IFS and PFS cannot handle. In this manuscript, the key innovation is to combine the traditional VIKOR model with q-RIVOFS to develop the q-rung interval-valued orthopair fuzzy VIKOR model. In the new developed model, to express more information, the attribute’s values in MAGDM problems are depicted by q-RIVOFNs. First of all, some basic theories and aggregation operators of q-RIVOFNs are simply introduced. Then we develop the origin VIKOR model to q-RIVOFS environment and briefly express the computing steps of this new established model. Thereafter, the effectiveness of the model is verified by an example of supplier selection of medical consumer products and through comparative analysis, the superiority of the new method is further illustrated.

Hesitant Neutrosophic Linguistic Sets and Their Application in Multiple Attribute Decision Making

In this paper, the hesitant neutrosophic linguistic set is first defined by extending a hesitant fuzzy set to accommodate linguistic terms and neutrosophic fuzzy values. Some operational laws are defined for hesitant neutrosophic linguistic fuzzy information. Several distance measures have been defined including generalized hesitant neutrosophic linguistic distance, generalized hesitant neutrosophic linguistic Hausdorff distance, and generalized hesitant neutrosophic linguistic hybrid distance. Some hesitant neutrosophic fuzzy linguistic aggregation operators based on the Choquet integral have been defined. A new multiple attribute decision making method for hesitant neutrosophic fuzzy linguistic information has been developed based on TOPSIS. In order to illustrate the feasibility and practical advantages of the new algorithm, we use it to select a company to invest. The new method is then compared with other methods.