In this paper, we define a new axiomatic definition of interval neutrosophic similarity measure, which is presented by interval neutrosophic number (INN). Later, the objective weights of various attributes are determined via Shannon entropy theory; meanwhile, we develop the combined weights, which can show both subjective information and objective information.

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Algorithms for Interval Neutrosophic Multiple Attribute Decision-Making Based on Mabac, Similarity Measure, and Edas

• A novel probabilistic dual hesitant fuzzy entropy is proposed. • Some novel probabilistic dual hesitant fuzzy distance measures are proposed. • The PDHFEPGMSM and PDHFWEPGMSM operators are proposed. • A novel MADM technique is proposed based on the PDHFWEPGMSM operator. • Case study of a SSS is presented to show the potentiality of the proposed technique. Sustainable suppliers selection is a typical multi-attribute decision-making (MADM) problem. MADM is a common problem in the field of decision-making, which is full of uncertainty and fuzziness. As a novel extension of fuzzy set (FS), probabilistic dual hesitant fuzzy set (PDHFS) can more fully and comprehensively express the uncertain and fuzzy information in MADM problems. In order to more effectively integrate the information of PDHFS, in this study, depend on extended power average (EPA) and generalized Maclaurin symmetric mean (GMSM) operators, probabilistic dual hesitant fuzzy extended power average generalized Maclaurin symmetric mean (PDHFEPMSM) operator and its weighted form (PDHFWEPMSM) which can consider the extremely data and the interrelationship among all decision attributes are defined and studied. Evidently, the novel proposed operators can obtain more accurate results than other existing methods. In addition, some precious properties and some special cases of these operators are discussed and studied. Afterwards, a novel PDHF MADM technique is developed based on the PDHFWEPGMSM and applied to MADM problem with probabilistic dual hesitant fuzzy elements (PDHFEs). Finally, a numerical example of sustainable suppliers selection is built to illustrate the practicality of the proposed MADM technique. Sensitivity analysis of parameters and further comparative analysis attest the flexibility and validity of the proposed MADM technique. The method presented in this paper can effectually solve the MADM problems which the decision-making information is expressed by PDHFEs and the attributes are interactive. 

A novel MADM technique based on extended power generalized Maclaurin symmetric mean operators under probabilistic dual hesitant fuzzy setting and its application to sustainable suppliers selection

Cpt-todim method for interval neutrosophic magdm and its application to third-party logistics service providers selection

EDAS method based on cumulative prospect theory for multiple attribute group decision-making under picture fuzzy environment

For the long-term development of shopping mall, the managers of shopping mall tend to build a new store to expand the enterprise’s market share in a new city. After holding a preliminary survey of the city, managers have initially identified five sites for construction. In order to select an optimal site, managers invite four experts who come from university, marking statistics, corporate executives and accounting to score sites. And they choose the best site on the basis of scores. The trait of EDAS method is to select an optimal alternative by using the distance of each alternative from the first-rank value. In this manuscript, we build the picture fuzzy EDAS method based on the cumulative prospect theory (PF-CPT-EDAS) for multiple attribute group decision-making (MAGDM) and it can help managers to choose an optimal alternative effectively. During the procedure of PF-CPT-EDAS means, we take advantage of the entropy means to calculate the original weights of all attributes. Ultimately, we testify the effectiveness of the novel model by comparing the overcome of PF-CPT-EDAS means with the results of PF-EDAS approach and other methods. 

In the era of uncertain information everywhere, the Probabilistic Hesitant Fuzzy sets (PHFs), utilizing the possible numbers and its possible membership degrees to descript decision-makers’ behavior, has been brought about widespread attention. Scholars from all over the world applied numerous approaches in this environment since Probabilistic Hesitant Fuzzy sets (PHFs) has been come up with, and there are still untapped territories. The TODIM (TOmada deDecisao Iterativa Multicrite´rio) method is a common decision-making method which is based on the prospect theory (PT). Unlike the other multiple criteria decision making (MCDM) methods, the TODIM method think over the bounded rationality of decision makers to choose the optimal alternative according to the decision maker’s psychological reality. In this essay, we introduce the Extended TODIM Based on Cumulative Prospect Theory (CPT) for probabilistic hesitant fuzzy multiple attributes group decision-making (MAGDM). In addition, the entropy is applied to calculate the weights between attributes. Finally, the developed method is used to solve the decision-making case study. To test the reasonability of this new method, we utilize a numerical case to compare the extended TODIM method with other methods.

TODIM Method Based on Cumulative Prospect Theory for Multiple Attributes Group Decision Making Under Probabilistic Hesitant Fuzzy Setting

Facing with a sea of fuzzy information, decision makers always feel it difficult to select the optimal alternatives. Probabilistic hesitant fuzzy sets (PHFs) utilize the possible numbers and the possible membership degrees to describe the behavior of the decision makers. though this environment has been introduced to solve problems using different methods, this circumstance can still be explored by using different method. This paper’ s aim is to develop the MABAC (Multi-Attributive Border Approximation area Comparison) decision-making method which based on cumulative prospect theory (CPT) in probabilistic hesitant fuzzy environment to handle multiple attributes group decision making (MAGDM) problems. Then the weighting vector of attributes can be calculated by the method of entropy. Then, in order to show the applicability of the proposed method, it is validated by a case study for buying a house. Finally, through comparing the outcome of comparative analysis, we conclude that this designed method is acceptable.

CPT-MABAC-Based multiple attribute group decision making method with probabilistic hesitant fuzzy information

An extended EDAS approach based on cumulative prospect theory for multiple attributes group decision making with probabilistic hesitant fuzzy information

Novel Gained and Lost Dominance Score Method Based on Cumulative Prospect Theory for Group Decision-Making Problems in Probabilistic Hesitant Fuzzy Environment

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. 

https://link.springer.com/content/pdf/10.1007/s00500-023-08132-w.pdf

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

Ningna Liao

Papers

TODIM Method Based on Cumulative Prospect Theory for Multiple Attributes Group Decision Making Under Probabilistic Hesitant Fuzzy Setting

CPT-MABAC-Based multiple attribute group decision making method with probabilistic hesitant fuzzy information

An extended EDAS approach based on cumulative prospect theory for multiple attributes group decision making with probabilistic hesitant fuzzy information

Novel Gained and Lost Dominance Score Method Based on Cumulative Prospect Theory for Group Decision-Making Problems in Probabilistic Hesitant Fuzzy Environment

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