Green supplier selection in steel industry with intuitionistic fuzzy Taxonomy method

Taxonomy method for green competitiveness evaluation of equipment manufacturing enterprises under picture 2-tuple linguistic environment

The fourth industrial revolution, represented by intelligence, networking and greening, is breeding and breaking through, and China is increasingly Focus on green development, public awareness of environmental protection, and small changes are able to fundamentally change our industrial organization. The equipment manufacturing industry is an industry to which our country attaches great importance, and equipment manufacturing enterprises, as microscopic subjects, want to contribute to the “13th Five-Year Plan”. Equipment manufacturing industry is a highly valued industry in China, equipment manufacturing enterprises as a microscopic subject, in order to the “Thirteenth Five-Year Plan” equipment manufacturing industry rose to inject a strong impetus, must make essential changes, embrace the green economy, green development, and enhance the green competitiveness of enterprises. The green competitiveness evaluation of equipment manufacturing enterprises is the classical multiple criterion group decision making (MCGDM). In this paper, depending on the Taxonomy method, Taxonomy method will be extended to picture 2-tuple linguistic sets (P2TLSs) to address some MCGDM issues. Some essential concepts of picture 2-tuple linguistic sets (P2TLSs) are briefly reviewed. In addition, integrating the Taxonomy method with P2TLSs, the Taxonomy method with P2TLNs is constructed and all calculating procedures are simply depicted. Eventually, an empirical application for green competitiveness evaluation of equipment manufacturing enterprises has been offered to demonstrate this novel method and some comparative analysis are also made to confirm the merits of developed method.

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.

EDAS method for multiple attribute group decision making under spherical fuzzy environment

Despite the importance of multi-attribute group decision making (MAGDM) problem in the field of optimal design, it is still a huge challenge to propose a solution due to its uncertainty and fuzziness. The spherical fuzzy sets (SFSs) can express vague and complicated information of MAGDM problem more widely. The Evaluation based on Distance from Average Solution (EDAS) method, as a highly practical decision-making method, has received extensive attention from researchers for solving MAGDM problem. In this paper, a spherical fuzzy EDAS (SF-EDAS) method is proposed to solve the MAGDM problem. Moreover, the entropy method is also introduced to determine objective weights, resulting in a more proper weight information. In addition, a practical example is settled by SF-EDAS method, which proves the excellent efficiency in applications of MAGDM problem. The SF-EDAS method provides an effective method for solving MAGDM problems under SFSs, and EDAS also provides a reference for further promotion of other decision-making environments.

An integrated methodology for commercial concrete supplier selection with intuitionistic fuzzy CPT-VIKOR

Aiming at the multi-attribute group decision-making (MAGDM) problem with unclear index weights values, and thinking about the bounded rational behavior of decision makers (DMs), we proposed a new improved CPT-VIKOR decision method under intuitionistic fuzzy (IF-CPT-VIKOR). Due to the emergence of special cases in IFSs, a new IFS score function and distance formula are defined. Meanwhile, the use of entropy weight method to obtain the weight information of indicators enhances the objectivity of the model. Furthermore, CPT is integrated into the IFS environment, which fully reflects the psychological behavior of DMs, and take advantage of the VIKOR method to determine the final sorting of the scheme. Finally, through the application cases of the commercial concrete supplier selection (CCSS) and the comparison with the existing authoritative methods to verify the feasibility and validity of the method.

An integrated intelligent decision systems for physical health evaluation of college students with fuzzy number intuitionistic fuzzy information

Physical Health is an important part of health education and health promotion in our country. Strengthen the research on the comprehensive evaluation of college students’ physical health, establish a representative, scientific, practical and operable index system, provide simple evaluation methods, scientifically evaluate the physical and health status of college students, and promote the scientific development of college students. Effective physical exercise, the development of good physical exercise habits and the promotion of school physical education teaching reform are of great significance. The physical health evaluation of College students is frequently viewed as the multiple attribute decision making (MADM) issue. In this paper, the generalized Heronian mean (GHM) operator and generalized weighted Heronian mean (GWHM) operator with fuzzy number intuitionistic fuzzy numbers (FNIFNs) is extended to build fuzzy number intuitionistic fuzzy GHM (FNIFGHM) operator and fuzzy number intuitionistic fuzzy GWHM (FNIFGWHM) operator. Then we depicted the FNIFWHM operator on the strength of this technique. In the rear, a case in point for Physical health evaluation of College students is described to prove the built methods.

Methodology for building material suppliers selection based on the intuitionistic fuzzy multiple attribute decision making method

The selection of suppliers is an important part of the construction of engineering projects in supply chain management. If the partners in the supply chain are reliable enough, they can promote the continuous progress of the supply and demand sides in the cooperation, thereby achieving a win-win situation, which is conducive to the realization of a virtuous cycle process. Material suppliers provide the required products and raw materials for the production and construction of enterprises. They are an important source of construction projects and occupy a very important position in the development of enterprises. The supply of high-quality products can lay a good foundation for the subsequent production and construction of the project, thereby promoting the smooth completion of the entire project. Therefore, rational evaluation and selection of suppliers has very important practical significance. The selection and application of building material suppliers is a classic multiple attribute decision making (MADM). In this paper, we introduced some calculating laws on intuitionistic fuzzy sets (IFSs), Hamacher sum and Hamacher product and further propose the induced intuitionistic fuzzy Hamacher power ordered weighted geometric (I-IFHPOWG) operator. Meanwhile, we also study some ideal properties of built operator. Then, we apply the I-IFHPOWG operator to deal with the multiple attribute decision making (MADM) problems under IFSs. Finally, an example for physical health literacy evaluation of College students is used to test this new approach.

An integrated methodology for utilization efficiency evaluation of college stadiums based on fuzzy number intuitionistic fuzzy multiple attribute group decision-making

In recent years, with the steady development of the national economy and the continuous improvement of people’s living standards, the desire for material pursuits has gradually transformed into the pursuit of spiritual food, and the attention to health and body is highly valued. It gave birth to and promoted the development of the sports industry. High-standard college stadiums provide many conveniences for students and faculty, and the construction and management of college stadiums are also an important part of the development of my country’s sports industry. However, there are still some drawbacks in the management mode and utilization efficiency of college stadiums. The utilization efficiency evaluation of college stadiums is frequently looked as the multiple attribute group decision-making (MAGDM) problem. Depending on the VIKOR process and fuzzy number intuitionistic fuzzy sets (FNIFSs), this paper designs a novel FNIF-VIKOR process to assess the resource utilization efficiency of college stadiums. First of all, some basic theories related to FNIFSs are briefly introduced. In addition, the weights of attributes are obtained objectively by utilizing CRITIC weight method. Afterwards, the conventional VIKOR process is extended to FNIFSs to obtain the final order of the alternative. Eventually, an application case for utilization efficiency evaluation of college stadiums and some comparative analysis are fully given. The results show that the built algorithms method is useful for assessing the resource utilization efficiency of college stadiums.

An integrated methodology for selecting the building material suppliers with interval-valued intuitionistic fuzzy information

At present, with the continuous changes in the market situation and the continuous improvement of the supply chain network structure, the competition in all walks of life has become more and more intense, which has risen from simple enterprise competition to competition in the entire supply chain. In the construction industry, the structure of the construction supply chain is more complex and diverse, and it is more necessary to select high-quality suppliers for sincere cooperation. This requires construction companies to establish a complete supply chain management system, select high-quality suppliers to achieve win-win cooperation and improve their competitiveness. Therefore, construction enterprises need to comprehensively consider various factors, build a reasonable and feasible evaluation index system according to their own demand for materials, and use appropriate evaluation methods to select material suppliers with specific advantages, so as to ensure the entire construction supply chain of the project. of smooth operation. In this paper, we introduced some calculating laws on interval-valued intuitionistic fuzzy sets (IVIFSs), Hamacher sum and Hamacher product and further propose the induced interval-valued intuitionistic fuzzy Hamacher ordered weighted average (I-IVIFHOWA) operator. Meanwhile, we also study some ideal properties of built operator. Then, we apply the I-IVIFHOWA operator to deal with the multiple attribute decision making (MADM) problems under IVIFSs. Finally, an example for selecting the building material suppliers is used to test this new approach.

Algorithms for multiple attribute group decision making with intuitionistic 2-tuple linguistic information and its application

Recently, the TODIM has been used to deal with multiple attribute decision making (MADM) problems. The intuitionistic 2-tuple linguistic sets (I2TLSs) are useful tools to depict uncertainty in MADM. This paper use TODIM method to solve MADM with the intuitionistic 2-tuple linguistic numbers (I2TLNs). Firstly, the concepts of I2TLNs are briefly presented, and classical TODIM for MADM are introduced. Then, the classical TODIM method is used to solve MADM with I2TLNs, and its important characteristic is to fully consider the decision makers’ bounded rationality which is a real action in MADM. And a comparative analysis is also given. Finally, a numerical example for service outsourcing providers selection is proposed.

Research on service quality evaluation of sports clubs with Pythagorean fuzzy information

In this paper, considering the traditional geometric operation laws and Pythagorean fuzzy information, a varies of new distance measures of Pythagorean fuzzy set are proposed, such as generalized Pythagorean fuzzy ordered geometric distance (GPFOWGD) measures and generalized Pythagorean fuzzy hybrid weighted geometric distance (GPFHWGD) measures. Besides, some special issues including Hamming distance, Euclidean distance and Hausdorff distance of these raised geometric distance measures are investigated. To testify the valid of these new presented distance measures, a decision-making model is built and illustrated by a mathematical calculation example to evaluate the service quality of sports clubs using Pythagorean fuzzy information. The results display that the approach is uncomplicated, valid and simple to compute. The example illustrates that the method presented in the paper can be used to deal with problems of uncertainty such as dynamic multiple attribute decision making.

VIKOR method for intuitionistic fuzzy multi-attribute group decision-making and its application to teaching quality evaluation of college English

The results of the nation-wide public college English tests and some other English tests held by the college itself are very valuable data for the assessment of the English teaching level. In the light of the selected and processed data and some other auxiliary approaches, the writer suggests that a modernized monitoring system be established to improve English teaching quality. Under this system, teachers’ and students’ English level can be evaluated in an objective way. Consequently, the subsequent measures such as teachers’ promotion as well as students’ development and employment and the evaluation of the quality of test-papers can be taken scientifically. We can solve the above issues with help of multi-attribute group decision making (MAGDM) method. Depending on the VIKOR steps and given intuitionistic fuzzy sets (IFSs), this paper devises the IF-VIKOR to assess the teaching quality of college English. In addition, the weights of attribute are derived through CRITIC method. Then, the VIKOR method is extended to IFSs to derive the order of each alternative. Therefore, all alternatives could be ranked and the best one can be identified. Eventually, we give an example of college English teaching quality evaluation, according to some comparison with other methods to make an analysis, the results show that the method proposed in such paper is effective and easy to compute.

Taxonomy method for multiple attribute group decision making based on interval-valued intuitionistic fuzzy with entropy

Interval-valued intuitionistic fuzzy set (IVIFS) is a flexible method to deal with uncertainty and fuzziness. For the past few years, extensive researches about the multi-attribute group decision making (MAGDM) problems based on IVIFSs has been extensively studied in many fields. In this study, the Taxonomy method based on IVIFSs (IVIF-Taxonomy) was proposed for MAGDM problems. For the sake of the objectivity of attribute weight, entropy is introduced into the proposed model. The IVIF-Taxonomy method fully considers the weight of the decision makers (DMs) and the homogeneity of the chosen alternatives, making it more realistic. In addition, we apply IVIF-Taxonomy method to fund selection to verify the validity of IVIF-Taxonomy method. Finally, the trustworthy of IVIF-Taxonomy method is proved by comparing with the aggregate operator, IVIF-TOPSIS method, IVIF-GRA method and modified IVIF-WASPAS method.

Taxonomy-based multiple attribute group decision making method with probabilistic uncertain linguistic information and its application in supplier selection

The optimal supplier selection in medical instrument industries could be considered a classical MAGDM issue. The probabilistic uncertain linguistic term sets (PULTSs) could depict uncertain information well and the Taxonomy method is appropriate to compare various alternatives according to their merits and utility degree from studied attributes. In such paper, we develop a Taxonomy method for probabilistic uncertain linguistic MAGDM (PUL-MAGDM) with the completely unknown attribute weights. Above all, the score function’s definition is utilized to derive the weights of attribute based upon the CRITIC method. In addition, the probabilistic uncertain linguistic development pattern (PULDP) is improved and the smallest development attribute value from the positive ideal solution under PULTSs is calculated to determine the optimal alternative. In the end, taking the supplier selection in medical instrument industries as an example, we demonstrate the usage of the developed algorithms. Based on this, the comparison of methods is conducted with existing methods, such as PUL-TOPSIS method, the PULWA operator, the PUL-EDAS method and the ULWA operator. The results verify that the decision-making framework is valid and effective for supplier selection. Thus, the advantage of this designed method is that it is simple to understand and easy to compute. The designed method can also contribute to the selection of suitable alternative successfully in other selection issues.

Research on teaching quality evaluation of college english based on the CODAS method under interval-valued intuitionistic fuzzy information

With the rapid development of China’s economic globalization in the new era, the demand for English majors is obviously on the rise, which puts forward new and higher requirements for application-oriented undergraduate colleges to train compound English majors. However, from the perspective of teaching quality evaluation of English majors in application-oriented undergraduate colleges, the results are not optimistic. Therefore, it is an important task for higher education research in China to explore the problems existing in the process of teaching quality evaluation for English majors in application-oriented undergraduate colleges and how to better train qualified and versatile talents for English majors to adapt to the economic and social development in the new era. The teaching quality evaluation of college English is frequently viewed as a multi-attribute group decision-making (MAGDM). Thus, a novel MAGDM method is used to tackle it. Depending on the conventional CODAS method and interval-valued intuitionistic fuzzy sets (IVIFSs), this paper designs a novel distance based IVIF-CODAS method to assess the teaching quality evaluation of college English. First of all, a related literature review is conducted. What’s more, some necessary theories related to IVIFSs are briefly reviewed. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria is decided objectively by utilizing CRITIC method. Afterwards, relying on novel distance measures between IVIFSs, the conventional CODAS method is extended to the IVIFSs to calculate assessment score of every alternative. Therefore, all alternatives can be ranked and the one with the best teaching quality. Eventually, an application about teaching quality evaluation of college English and some comparative methods have been employed to show the superiority of the developed method. The results illustrate that the defined framework is very useful for assessing the teaching quality of college English.

Some self-evaluation models of enterprise’s credit based on some probabilistic double hierarchy linguistic aggregation operators

Probabilistic double hierarchy linguistic term set (PDHLTS) can not only express the complex linguistic information that the probabilistic linguistic term set (PLTS) cannot express, but also reflect the frequency or importance of linguistic term set (LTS)that cannot be reflected by the double hierarchy linguistic term set (DHLTS). It is an effective tool to deal with multiple attribute group decision making (MAGDM) problems. Therefore, in this paper, we propose several aggregation operators which can aggregate PDHLTS information and apply them to MAGDM problems. Firstly, the basic notion of PDHLTS is reviewed, and the distance formula and algorithm of PDHLTS are defined; then, extant weighted averaging (WA) operator, weighted geometric(WG) operator and power weighted averaging (PWA) operator, power weighted geometric(PWG) operator to PDHLTS, and establish probability double hierarchy linguistic weighted averaging (PDHLWA) operator, probability double hierarchy linguistic weighted geometric (PDHLWG) operator, probability double hierarchy linguistic power weighted averaging (PDHLPWA) operator, probability double hierarchy linguistic power weighted geometric (PDHLPWG) operator; in addition, The idempotency, boundedness and monotonicity of these aggregation operators are studied; what’s more, those aggregation operators are proposed to establish the enterprise credit self-evaluation model; Finally, compared with the available probabilistic double hierarchy linguistic MAGDM methods, the defined model is proved to be scientific and effective.

Research on the teaching quality evaluation of physical education with intuitionistic fuzzy TOPSIS method

Under the background of the national fitness craze, the demand space for social sports professionals is constantly expanding. However, according to the author’s investigation, the overall situation shows that the number of high-quality social sports professionals in Chinese colleges and universities is relatively small. Among them, the unsound teaching quality evaluation system of social sports major is one of the important reasons affecting the cultivation of high-quality talents, so it is imperative to construct a sound teaching quality evaluation system of social sports major. At the same time, the perfect social physical education teaching quality evaluation system is an important basis for teachers’ teaching job evaluation and strengthening teachers’ management. And it is frequently considered as a multi-attribute group decision-making (MAGDM) issue. Thus, a novel MAGDM method is needed to tackle it. Depending on the conventional TOPSIS method and intuitionistic fuzzy sets (IFSs), this essay designs a novel intuitive distance based IF-TOPSIS method for teaching quality evaluation of physical education. First of all, a related literature review is conducted. What’s more, some necessary theories related to IFSs are briefly reviewed. In addition, since subjective randomness frequently exists in determining criteria weights, the weights of criteria are decided objectively by utilizing CRITIC method. Afterwards, relying on novel distance measures between IFNs, the conventional TOPSIS method is extended to the intuitionistic fuzzy environment to calculate assessment score of each alternative. Eventually, an application about teaching quality evaluation of physical education and some comparative analysis have been given. The results think that the designed method is useful for teaching quality evaluation of physical education.

Algorithms for MAGDM with intuitionistic fuzzy sets and their application for evaluating the green technological innovation ability of the enterprises

The dual generalized Bonferroni mean (DGBM) operator is a meaningful decision-making tool which can consider the relationship between any numbers of being fused arguments and has been applied to many MAGDM domains in past few years. The intuitionistic fuzzy sets (IFSs), which is characterized by the functions of membership degree and non-membership degree, has been investigated by numerous scholars. In this manuscript, combine the DGBM operator and IFSs, the major contribution and objective of the work is to develop two new aggregation operators: the dual generalized intuitionistic fuzzy BM (DGIFBM) operator and the dual generalized intuitionistic fuzzy weighted BM (DGIFWBM) operator. The last, we give an application example for evaluating the green technological innovation ability of the enterprises and some comparative analysis to testify the effective and scientific of our developed methods.

A Hybrid MADM Model for Newly Graduated Nurse's Competence Evaluation and Improvement

Nursing departments in hospitals must evaluate the practical competency of newly graduated nurses and assist them to increase their competence. Competency assessments often consider multiple qualitative attributes and use expert knowledge as the basis for decision-making. This study proposes a hybrid multiple attribute decision-making (MADM) model that determines practical competency of the newly graduated nurse as an evaluation framework. A causal influence-network diagram (CIND) and influential weights are obtained from nursing experts' clinical experience using the decision-making trial and evaluation laboratory (DEMATEL)-based analytical network process analysis (DANP). The MOORA-AS method is then used to evaluate the ability expectation ratio-gap for newly graduated nurses in practice. The CIND is used to allow each newly graduated nurse to reduce the performance ratio-gaps between the current level and the aspirational level from a systematic perspective. The empirical data applies to a third-class and a first-class hospital in China. The results show that the proposed hybrid MADM model has reliable results and allows nursing department decision-makers/managers to easily evaluate and systematically improve competencies for newly graduated nurses.