Multiple Attribute Group Decision Research Articles

An integrated decision-making methodology for green supplier selection based on the improved IVIF-CPT-MABAC method

Green supply chain management attaches great importance to the coordinated development of social economy and ecological environment, and requires enterprises to consider environmental protection factors in product design, packaging, procurement, production, sales, logistics, waste and recycling. Suppliers are the “source” of the entire supply chain, and the choice of green suppliers is the basis of green supply chain management, and their quality will directly affect the environmental performance of enterprises. The green supplier selection is a classical multiple attribute group decision making (MAGDM) problems. Interval-valued intuitionistic fuzzy sets (IVIFSs) are the extension of intuitionistic fuzzy sets (IFSs), and are utilized to depict the complex and changeable circumstance. To better adapt to complex environment, the purpose of this paper is to construct a new method to solve the MAGDM problems for green supplier selection. Taking the fuzzy and uncertain character of the IVIFSs and the psychological preference into consideration, the original MABAC method based on the cumulative prospect theory (CPT) is extended into IVIFSs (IVIF-CPT-MABAC) method for MAGDM issues. Meanwhile, the method to evaluate the attribute weighting vector is calculated by CRITIC method. Finally, a numerical example for green supplier selection has been given and some comparisons is used to illustrate advantages of IVIF-CPT-MABAC method and some comparison analysis and sensitivity analysis are applied to prove this new method’s effectiveness and stability.

Sustainable competitiveness evaluation of regional financial centers with fuzzy number intuitionistic fuzzy TODIM algorithms

The competitiveness evaluation of regional financial centers is frequently looked as the multiple attribute group decision-making (MAGDM) problem. Based on the TODIM method and fuzzy number intuitionistic fuzzy sets (FNIFS), this paper proposes a new FNIF-TODIM method to evaluate the competitiveness of regional financial centers. First, some basic theories related to FNIFS are briefly introduced. In addition, the weights of the attributes are obtained objectively using the CRITIC weighting method. Then, the traditional TODIM method is extended to FNIFS to obtain the final order of alternatives. As a result, all alternatives can be ranked and the best one for the competitiveness assessment of regional financial centers can be identified. Finally, an example for competitiveness evaluation of regional financial centers and some decision comparative analysis is listed. The results show that the established algorithmic approach is useful. The main works of this work are: (1) the paper constructs the FNIF-TODIM method for the evaluation of the competitiveness of regional financial centers; (2) the established method is illustrated by a case study for competitiveness evaluation of regional financial centers; and (3) some comparisons prove the rationality and advantages.

A novel approach based on similarity measure for the multiple attribute group decision-making problem in selecting a sustainable cryptocurrency

Environmental impact and sustainability challenges in the cryptocurrencies has become increasingly examined in the literature. However, studies of the multiple attribute group decision making (MAGDM) method for major selection of cryptocurrencies in advancing sustainability are still at an early stage. In particular, research on the fuzzy-MAGDM method in the evaluation of sustainability in cryptocurrencies is scarce. This paper adds contributions by developing a novel MAGDM approach to evaluate the sustainability development of major cryptocurrencies. It proposes a similarity measure for interval-valued Pythagorean fuzzy numbers (IVPFNs) based on whitenisation weight function and membership function in grey systems theory for IVPFNs. It further developed a novel generalised interval-valued Pythagorean fuzzy weighted grey similarity (GIPFWGS) measure approach to provide a more rigorous evaluation in complex decision marking problem with embedding ideal solution and membership degree. It also conducts a sustainability evaluation model of major cryptocurrencies as a numerical application and performs a robustness assessment with different variations of the expert’s weight to test how different values of parameter θ can affect the ranking results of alternatives. The results suggest that Stellar is the most sustainable cryptocurrency, while Bitcoin with its intensive energy consumption, high mining cost and high computing power provides the least effective support for its sustainable development. A comparative analysis with the average value method and Euclidean distance method was performed to validate the reliability of the proposed decision-making model and provides evidence that the GIPFWGS has better fault tolerance.

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 centersite selection (MLCSS) is given to validate the proposed method.

A Group Consensus Model for Multiple Attributes Group Decision Making with Interval Belief Distribution and Interval Distributed Preference Relation

A Group Consensus Model for Multiple Attributes Group Decision Making with Interval Belief Distribution and Interval Distributed Preference Relation

IVNN-Taxonomy method for teaching effect evaluation of “micro-ideological and political” model in medical colleges and universities

How to make good use of new network technology and design the classroom teaching of a course needs to be based on the teaching object, teaching content, and the teacher’s mastery of the technology and teaching platform. In teaching design, scholars also put forward different teaching links based on their own teaching experience. The cooperative learning links should be designed in college teaching. To build a positive and interdependent organizational structure and an equal and democratic learning atmosphere will help students to stimulate their learning motivation and sense of responsibility. The fuzzy evaluation of the teaching effect of the “micro-ideological and political” model in medical colleges and universities is viewed as the multiple attribute group decision making (MAGDM) issue. In such paper, Taxonomy method is designed for solving the MAGDM under interval-valued neutrosophic sets (IVNSs). First, the score function of IVNSs and Criteria Importance Though Intercrieria Correlation (CRITIC) method is used to derive the attribute weights. Second, then, the interval-valued neutrosophic numbers Taxonomy (IVNN-Taxonomy) method is built to deal with MAGDM problem. Finally, a numerical example for teaching effect evaluation of the “micro-ideological and political” model in medical colleges and universities is given to illustrate the built method.

An efficient method for ideological and political education quality evaluation of colleges and universities with 2-tuple linguistic neutrosophic sets

Improving college students’ satisfaction with the teaching quality of ideological and political theory courses in colleges and universities is the need to promote college students to consciously fulfill their ideological and political quality, and it is also the need to further form a strong driving force for the teaching reform of ideological and political theory courses in colleges and universities. The requirements of teaching level are also the requirements to further enhance the competitiveness of colleges and universities. The ideological and political education quality (IPEQ) evaluation of college students is looked as multiple attribute group decision-making (MAGDM) problem. In this paper, the 2-tuple linguistic neutrosophic TOPSIS (2TLN-TOPSIS) model is built based on the traditional TOPSIS and 2-tuple linguistic neutrosophic sets (2TLNSs). Firstly, the 2TLNSs is introduced. Then, combine the TOPSIS model with 2TLNSs, the 2TLN-TOPSIS model is established for MAGDM. Finally, a numerical example for IPEQ evaluation of College students have been given and some comparisons are also conducted to further illustrate advantages of the 2TLN-TOPSIS method.

Uncertainty measure for Z-soft covering based rough graphs with application

Soft graphs are an interesting way to represent specific information. In this paper, a new form of graphs called Z-soft covering based rough graphs using soft adhesion is defined. Some important properties are explored for the newly constructed graphs. The aim of this study is to investigate the uncertainty in Z-soft covering based rough graphs. Uncertainty measures such as information entropy, rough entropy and granularity measures related to Z-soft covering-based rough graphs are discussed. In addition, we develop a novel Multiple Attribute Group Decision-Making (MAGDM) model using Z-soft covering based rough graphs in medical diagnosis to identify the patients at high risk of chronic kidney disease using the collected data from the UCI Machine Learning Repository.

Model for evaluating the airline business operations capability based on 2TLPF-TOPSIS method and entropy weight

Based on the traditional TOPSIS method and 2-tuple linguistic Pythagorean fuzzy numbers (2TLPFNs), this paper builds a novel 2TLPF-TOPSIS method that combines cumulative prospect theory (CPT) to cope with the multiple attribute group decision-making (MAGDM). This new method takes into account the decision-makers’ mind and the uncertainty of decision-making, and is more in line with the real decision-making environment. First, this paper briefly reviews some necessary theories related to PFS, as well as the calculation rules and comparison methods of 2TLPFNs. Then, since there is often subjective randomness when determining the weight, the entropy method is utilized to objectively determine the weight. After that, give the specific calculation steps of the new method. In order to show the effectiveness of the new method, apply it into a specific numerical example about evaluating airline business operations capability, and compare it with the other four different methods. The ranking results depict that the new method designed is effective and reasonable, and has good application value of MAGDM problems.

Maclaurin symmetric mean aggregation operators based on novel Frank T-norm and T-conorm for intuitionistic fuzzy multiple attribute group decision-making

Multi-attribute group decision-making (MAGDM) is an interesting technique to find the most optimal alternative among comparative alternatives. Several authors put forward to MAGDM by introducing different fuzzy frameworks and also different tools to deal with fuzzy information. Intuitionistic fuzzy set (IFS) is the fuzzy framework that deals with the uncertainty in MAGDM. Due to their flexibility and generality, Frank t-norm (FTNM) and t-conorm (FTCNM) play an essential role in information fusion. Moreover, as the generalization of some mean operators, the Maclaurin symmetric mean (MSM) operator considers the relationship between multi-criteria arguments, especially in MAGDM. This article aims to develop some MSM aggregation operators (AOs) for the intuitionistic fuzzy set (IFS) based on FTNM and FTCNM and to apply newly developed AOs in the MAGDM. To utilize the MAGDM algorithm, first, we defined the MSM by using the FTNM and FTCNM in the environment of IFS. Then we proposed intuitionistic fuzzy (IF) Frank MSM (IFFMSM) and IF Frank weighted MSM (IFFWMSM) operators. Then, the fundamental properties of these AOs are stated and proved. Then, the strategy is given that accounts for the application of the newly developed family of AOs. Further, freshly defined operators are applied to the MAGDM problem with the help of an example where the risk factors of the construction industry are assessed. To cope with the significance, the proposed AOs are compared with some existing AOs. This study also addresses the variation of these AOs' behavior based on the interpretation of sensitive parameters.

Modified CPT-TODIM method for evaluating the development level of digital inclusive finance under probabilistic hesitant fuzzy environment.

Unlike traditional finance, digital inclusive finance is committed to integrating digital technology with the financial industry to bring groups originally excluded from traditional finance back into formal financial services and provide financial services at reasonable prices and matching needs for all social classes. Digital inclusive finance can effectively reduce the financing costs of SMEs, improve the external financing environment of enterprises, and provide more convenient, equal and perfect financial services for enterprises by using technical support such as "big data + artificial intelligence". The development level of digital inclusive finance is a classical multiple attributes group decision making (MAGDM). The Probabilistic hesitant fuzzy sets (PHFSs), which utilize the possible values and its possible membership degrees to depict decision-makers' behavior in different conditions, has been paid great attention. Though numerous methods have been applied in this environment since PHFSs has been introduced, there are still new fields to be explored. In this paper, we introduce the Cumulative Prospect Theory TODIM (CPT-TODIM) for probabilistic hesitant fuzzy MAGDM(PHF-MAGDM). Meanwhile, the information of entropy is utilized to calculate the weight of attributes, which is used to improve the classical TODIM method. At last, we utilize a numerical case for evaluating the development level of digital inclusive finance to compare the extended CPT-TODIM method with the classical TODIM method.

Extended QUALIFLEX method for electronic music acoustic quality evaluation based on the picture fuzzy multiple attribute group decision making

In the past, different useful extensions of fuzzy sets were established by the researchers to manage the vagueness and uncertainty in various practical problems. Usually, the real numbers are utilized to express the decision information, but it is noted that the description of attributes using picture fuzzy sets (PFSs) proves to be more appropriate. As a powerful decision tool, PFSs provides more decision information that requires the application of some specific situations more types of response of human ideas: yes, contain, no, reject. QUALIFLEX (qualitative flexible multiple criteria method), is one of the well-known outranking methods to solve the multiple attribute group decision making (MAGDM) problems with crisp numbers. The QUALIFLEX method can perfectly address the complex MAGDM problems where a lot of attributes are utilized to assess a limited number of alternatives. The electronic music acoustic quality evaluation is a classical MAGDM. This paper proposes and utilizes the QUALIFLEX to develop the picture fuzzy QUALIFLEX(PF-QUALIFLEX) method for MAGDM. The current study is mainly devoted to explore and extend the measurement of alternatives and ranking according to the QUALIFLEX under the background of PFSs. Furthermore, an example to evaluate the electronic music acoustic quality is handled through the proposed method to substantiate the extended approach.

Method for 2-tuple linguistic neutrosophic number MAGDM and applications to physical education teaching quality evaluation in colleges and universities

The quality of physical education (PE) teaching in colleges and universities is the basis for the development of PE disciplines in colleges and universities, so currently thinking about how to effectively improve the quality of PE teaching in colleges and universities has become the first and foremost problem for many college and university PE departments to solve. In order to solve this problem, it is necessary to build a reasonable and scientific evaluation and monitoring system of PE teaching quality, because only by establishing an effective evaluation and monitoring system of teaching quality can we evaluate and supervise all the PE operation properly and scientifically, and then give feedback in the process of evaluation and supervision, such evaluation and monitoring system can greatly promote the continuous improvement of PE teaching quality in colleges and universities. This is also one of the most effective means to improve the quality of PE and achieve the goal of PE in colleges and universities. The PE teaching quality evaluation in Colleges and Universities is frequently viewed as the multiple attribute group decision making (MAGDM) issue. In this paper, the 2-tuple linguistic neutrosophic number grey relational analysis (2TLNN-GRA) method is built based on the traditional grey relational analysis (GRA) and 2-tuple linguistic neutrosophic sets (2TLNNSs). Then, a numerical example for PE teaching quality evaluation in Colleges and Universities has been given and some comparisons is used to illustrate advantages of 2TLNN-GRA method.

Q-rung orthopair fuzzy bi-direction Choquet integral based on TOPSIS method for multiple attribute group decision making

q-rung orthopair fuzzy bi-direction Choquet integral based on TOPSIS method for multiple attribute group decision making

Multivalued neutrosophic power partitioned Hamy mean operators and their application in MAGDM.

The novel multivalued neutrosophic aggregation operators are proposed in this paper to handle the complicated decision-making situations with correlation between specific information and partitioned parameters at the same time, which are based on weighted power partitioned Hamy mean (WMNPPHAM) operators for multivalued neutrosophic sets (MNS) proposed by combining the Power Average and Hamy operators. Firstly, the power partitioned Hamy mean (PPHAM) is capable of capture the correlation between aggregation parameters and the relationship among attributes dividing several parts, where the attributes are dependent definitely within the interchangeable fragment, other attributes in divergent sections are irrelevant. Secondly, because MNS can effectively represent imprecise, insufficient, and uncertain information, we proposed the multivalued neutrosophic PMHAM (WMNPHAM) operator for MNS and its partitioned variant (WMNPPHAM) with the characteristics and examples. Finally, this multiple attribute group decision making (MAGDM) technique is proven to be feasible by comparing with the existing methods to confirm this method's usefulness and validity.

Model-based evaluation for online food delivery platforms with the probabilistic double hierarchy linguistic EDAS method

In recent years, with the rapid expansion of internet technology, the number of online food delivery services has grown. Despite the ease, a poor online food delivery platform (OFP) produces all kinds of problems for individuals. A comprehensive and reasonable evaluation of online food delivery is of great significance. Therefore, this study establishes an OFP evaluation model based on the probabilistic double hierarchy linguistic EDAS (PDHL-EDAS) method for multiple attribute group decision-making (MAGDM). Then the CRITIC model is introduced to derive the objective weight and the cumulative prospect theory is leaded to obtaining the cumulative weight of PDHLTS. In furthermore, the benefits and applicability of the PDHL-EDAS method are illustrated by solving practical MAGDM problems concerning the evaluation of OFPs. Lastly, the proposed method is verified by comparison with other MAGDM methods, in addition to discussing potential future research directions.

Performance evaluation of family business strategic transition based on the 2-tuple linguistic neutrosophic number multiple attribute group decision making

Since 2010, China’s traditional industry has entered a critical stage of development and enterprise reform and development is imminent. Product homogenization is serious in this market, so that the competition among enterprises is fierce. At the same time, international brands continue to enter the Chinese consumption market, which intensifies the competition and seriously squeezes the market share of Chinese local brands. However, the popularization and development of the Internet and the change of people’s consumption concept and level make the market put forward higher requirements for the development of business operation and many traditional family enterprises have embarked on the road of transformation. It is of great significance and value to clarify the influence of internal factors of family enterprises on strategic transformation. The performance evaluation of family business strategic transition is really a multiple attribute group decision making (MAGDM) problems. In this paper, the 2-tuple linguistic neutrosophic number grey relational analysis (2TLNN-GRA) method is proposed along with on the traditional grey relational analysis (GRA) and 2-tuple linguistic neutrosophic sets (2TLNNSs). Firstly, the 2TLNNSs is introduced. Then, combine the traditional fuzzy GRA model with 2TLNNSs information, the 2TLNN-GRA method is established and the computing steps for MAGDM are built. Finally, a numerical example for performance evaluation of family business strategic transition has been given and some comparisons is used to illustrate advantages of 2TLNN-GRA method.

Dynamic Chaotic Multi-Attribute Group Decision Making under Weighted T-Spherical Fuzzy Soft Rough Sets

In this article, the parameter of the decision maker’s familiarity with the attributes of the alternatives is introduced for the first time in dynamic multi-attribute group decision making to avoid the disadvantages arising from the inappropriate grouping of decision makers. We combine it with fuzzy soft rough set theory and dynamic multi-attribute-grouping decision making to obtain a new decision model, i.e., dynamic chaotic multiple-attribute group decision making. Second, we provide an algorithm for solving this model under a weighted T-spherical fuzzy soft rough set, which can not only achieve symmetry between decision evaluation and fuzzy information but also establish a good symmetrical balance between decision makers and attributes (evaluation indexes). Finally, a specific numerical computation case is proposed to illustrate the convenience and effectiveness of our constructed algorithm. Our contributions to the literature are: (1) We introduced familiarity for the first time in dynamic multi-attribute group decision making. This makes our given dynamic chaotic multi-attribute group decision-making (DCMAGDM) model more general and closer to the actual situation; (2) we combined dynamic chaotic multi-attribute group decision making with T-spherical fuzzy soft rough set theory to make the model more realistic and reflect the actual situation. In addition, our choice of T-spherical fuzzy soft rough set allows the decision maker to engage in a sensible evaluation rather than sticking to numerical size choices; and (3) we constructed a new and more convenient sorting/ranking algorithm based on weighted T-spherical fuzzy soft rough sets.

MABAC method for multiple attribute group decision making under single-valued neutrosophic sets and applications to performance evaluation of sustainable microfinance groups lending.

As an important supplement to my country's financial institutions, micro-loan companies serve "agriculture, rural areas and farmers", small and micro enterprises, and individuals, to a certain extent, alleviating the financing difficulties of such groups and regulating private finance. However, micro-loan companies only lend but do not deposit. In the process of lending, due to inadequate risk management, the risk problem has become increasingly prominent. With the continuous growth of the loan amount of rural credit and the continuous increase of microfinance groups lending customers, it faces certain problems in its risk management, which increases the risks of the company in all aspects. The performance evaluation of sustainable microfinance groups lending is a classical MAGDM issues. In such paper, the Hamming distances of single-valued neutrosophic sets (SVNSs) and maximizing deviation method (MDM) is used to obtain the attribute weights and the single-valued neutrosophic numbers MABAC(SVNN-MABAC) method is structured for MAGDM under SVNSs. Finally, an example about performance evaluation of sustainable microfinance groups lending and some comparative decision analysis are given to proof the SVNN-MABAC.

A mathematical programming method based on prospect theory for online physician selection under an R-set environment

This study develops an R-mathematical programming method for multiple attribute group decision-making (MAGDM) problems with assessment values of alternatives and truth degrees of pairwise alternative comparisons represented by R-sets while the decision maker holds subjective bounded rationality. First, a novel scalar multiplication operation and defuzzification of R-sets are proposed to allow the use of R-sets in MAGDM problems. Subsequently, based on prospect theory and R-sets, a new technique is proposed to compute the individual overall prospect value of an alternative by simultaneously considering the positive ideal solution (PIS) and negative ideal solution (NIS). Additionally, the R-group consistency index (R-GCI) and R-group inconsistency index (R-GII) are defined using the individual overall prospect values of alternatives. The decision makers’ weights, attribute weights, PIS, and NIS are estimated by establishing a novel R-mathematical programming model, which is solved by the external archive-based constrained state transition, while the collective overall prospect values are computed to derive the final ranking order of alternatives. Thus, a new R-LINMAP method is developed to solve MAGDM. A practical instance concerning online physician selection is provided with the corresponding sensitive and comparative analyses to verify the applicability, validity, and superiority of the developed method.