Multiple Attribute Group Decision Research Articles

AN INTEGRATED DECISION SUPPORT SYSTEM FOR STOCK INVESTMENT BASED ON SPHERICAL FUZZY PT-EDAS METHOD AND MEREC

The stock investment selection could be deemed as a classic multiple attribute group decision making (MAGDM) problem involving multiple conflicts and interleaved qualitative and quantitative attributes. Spherical fuzzy sets (SFSs) can excavate the potential vagueness and intricacy in MAGDM more effectively and deeply. This article we propose an integrated decision support system (IDSS) based on SFSs, prospect theory (PT), distance from average solution (EDAS) method and the MEthod based on the Removal Effects of Criteria (MEREC). The proposed IDSS, called SF-PT-EDAS-MEREC model, uses SFSs to describe the uncertain and obscure assessment information of DMs. The combination of PT and EDAS (PT-EDAS) method adequately captures DMs’ psychological behavior characteristics to execute more reasonable alternative evaluation. The MEREC is utilized to efficaciously obtain unknown attribute weights. In addition, this paper also presents a novel score function to compare spherical fuzzy numbers (SFNs) more directly and efficiently. Eventually, in order to illustrate the practicability of the proposed IDSS, two numerical examples of stock investment selection are employed to achieve this. Meanwhile, the comparative study with existing approach further demonstrates the effectiveness and superiority of SF-PT-EDAS-MEREC model.

A novel group decision making model based on Interval neutrosophic sets for product modeling design quality evaluation

The energy consumption of mechanical products in China is enormous, and the energy utilization rate is low, which is increasingly receiving people’s attention. Conducting product design for energy optimization is of great significance for improving energy utilization efficiency. The scheme design of a product is the key to achieving innovation in product design, and the evaluation and decision-making of the design scheme directly affect the results of the later stage of the design. Therefore, correctly evaluating and making reliable decisions on product design schemes that are oriented towards fuzzy decision optimization is an important aspect of product innovation conceptual design. The product modeling design quality evaluation is a multiple attribute group decision making (MAGDM) problems. Recently, the Combined Compromise Solution (CoCoSo) method and information entropy method has been employed to cope with MAGDM issues. The interval neutrosophic sets (INSs) are employed as a tool for portraying uncertain information during the product modeling design quality evaluation. In this paper, the CoCoSo method is designed for MAGDM under INSs. Then, the interval neutrosophic numbers CoCoSo (INN-CoCoSo) method based on the Hamming distance and Euclidean distance is built for MAGDM. The information Entropy method is employed to produce the weight information based on the Hamming distance and Euclidean distance under INNSs. Finally, a practical numerical example for product modeling design quality evaluation is supplied to show the INN-CoCoSo method. The main contributions of this paper are constructed: (1) This paper builds the novel MAGDM based on CoCoSo model under INSs; (2) The information Entropy method is employed to produce the weight information based on the Hamming distance and Euclidean distance under INNSs; (3) The new MAGDM method is proposed for product modeling design quality evaluation based on INN-CoCoSo.

A novel approach to employment quality evaluation of college graduates with probabilistic linguistic MAGDM

With the continuous extension and deepening of college education reform, the research on the future employment of college students and the evaluation of employment quality has become a major focus topic. The traditional evaluation system for the employment quality of college graduates is relatively outdated and unitary, lacking a vision of the future development status of college graduates, as well as an effective understanding and mastery of the overall feedback and evaluation of the entire employment market for college graduates. Moreover, most colleges and universities mainly focus on the level of competence that college graduates should achieve five years after graduation from college in terms of talent cultivation goals, The lack of specific evaluation work for long-term employment tracking of graduates has resulted in universities being unable to grasp and understand the degree of fit and matching between the comprehensive abilities of university graduates and the future employment market, and thus unable to provide effective feedback and summary of talent cultivation and innovation strategies. Therefore, it is imperative to comprehensively innovate the employment quality evaluation system and methods for college graduates. The employment quality evaluation of college graduates is a classical multiple attribute group decision making (MAGDM) problems. Recently, the TODIM and VIKOR method has been used to cope with MAGDM issues. The probabilistic linguistic term sets (PLTSs) are used as a tool for characterizing uncertain information during the employment quality evaluation of college graduates. In this manuscript, the probabilistic linguistic TODIM-VIKOR (PL-TODIM-VIKOR) method is built to solve the MAGDM under PLTSs. In the end, a numerical case study for employment quality evaluation of college graduates is given to validate the proposed method.

Modified EDAS method for spherical fuzzy multiple attribute group decision making and applications to English classroom teaching quality evaluation

Classroom teaching is an important link related to the quality of teaching and talent cultivation. In the implementation of classroom teaching, we should fully attach importance to the main position of students, the role of educational technology and information technology in teaching activities, make use of the latest educational ideas and educational concepts, and combine the actual situation of college English teaching and college English teaching in China, and attach importance to foreign language teaching theories and practices at home and abroad, Establish monitoring indicators and monitoring system for college English teaching quality. Under the guidance of effective monitoring indicators, teachers’ teaching concepts can be updated and improved in real time to achieve better teaching results. At the same time, the quality assurance and monitoring system of college English teaching can be continuously improved to make it more perfect. The English classroom teaching quality evaluation could be deemed as a classic multiple attribute group decision making (MAGDM) problem. Spherical fuzzy sets (SFSs) can excavate the uncertainty and fuzziness in MAGDM more effectively and deeply. This article we first present a novel score function to compare spherical fuzzy numbers (SFNs) more directly and efficiently. Then, on basis of evaluation based on distance from average solution (EDAS), a novel spherical fuzzy EDAS (SF-EDAS) method is built for dealing with MAGDM. Moreover, when the attribute weights are completely unknown, the MEthod based on the Removal Effects of Criteria (MEREC) is extended to spherical fuzzy environment (SFE) to reasonably acquire the attribute weights. Finally, SF-EDAS approach is used for English classroom teaching quality evaluation to prove practicability of the developed method and compare SF-EDAS method with existing methods to further demonstrate its legitimacy and superiority.

An integrated fuzzy group decision-making model for construction enterprise contractor selection based on EDAS method and Information entropy

With the rapid development of China’s construction industry, the competition in the construction industry is becoming increasingly fierce. Enterprises need to continuously improve their competitiveness in the market. Some non-core businesses can be outsourced to professional contractors. At present, contractors have more and more influence on the operation and development of enterprises. Whether it is the construction period or the quality of the project, it will have a greater impact on the operation of the construction project. In the environment of increasingly fierce market competition and increasing project quality requirements, for the construction project contracting enterprises, in order to achieve the goal of low cost and high quality, it is necessary to select the most suitable contractor on the basis of comprehensive consideration of multiple factors. The construction enterprise contractor selection is a classical multiple attribute group decision making (MAGDM) problem. In recent years, the MAGDM problem has become an important research field in modern decision science. This paper extends the EDAS method to the 2-tuple linguistic Pythagorean fuzzy sets (2TLPFSs). On the basis of the original EDAS method, 2-tuple linguistic Pythagorean fuzzy EDAS (2TLPF-EDAS) is built for MAGDM. Finally, a case study for construction enterprise contractor selection and some comparative analysis with the other methods show that the new method proposed in this paper is effective, reasonable and accurate.

Integrated MAGDM framework based on spherical fuzzy sets for teaching quality evaluation of ideological and political courses in universities

With the rapid development of society, ideological and political education courses have occupied a very important position in various courses in major universities, playing a series of important functions and roles in student quality education, excellent quality cultivation, and other aspects. In the new era, the evaluation and assessment of ideological and political education quality is not only the primary factor to improve the teaching quality of ideological and political education courses in universities, but also an important means to promote the deepening reform of ideological and political education. However, there are many problems in the process of evaluating the quality of ideological and political education in colleges and universities at present, such as the deviation in understanding the importance of evaluation, the relatively single evaluation method, and the low quality of application of evaluation results. The teaching quality evaluation of ideological and political courses in universities is a classical multiple attribute group decision making (MAGDM). Spherical fuzzy sets (SFSs) provide more free space for decision makers (DMs) to express preference information during the teaching quality evaluation of ideological and political courses in universities. Therefore, this paper we first extend partitioned Maclaurin symmetric mean (PMSM) operator and IOWA operator to SFSs and develop induced spherical fuzzy weighted PMSM (I-SFWPMSM) operator. Subsequently, a new MAGDM method is established based on I-SFWPMSM operator and SFNWG operator under SFSs. Finally, a numerical example for teaching quality evaluation of ideological and political courses in universities is used to illustrate the proposed method.

An integrated group decision-making method for brand packaging design effect evaluation based on the 2-tuple linguistic Pythagorean fuzzy sets

In the current era of economic and cultural globalization, the demand for packaging design is increasing, and the packaging design requirements for brands and products in the entire consumer market are becoming increasingly strict and refined. Designers are facing one greater challenge after another. Packaging design, as a comprehensive discipline that integrates commerce, culture, and art, diverse cultural forms and elements will run through the entire process of brand packaging design. Good products need to be sold through good channels in order to achieve greater value. As a bridge connecting products and the market, the role of packaging design is even more evident. It can not only improve the recognition of products, but also help enterprises stand out among many similar products, thereby increasing product value. The brand packaging design effect evaluation is a classical multiple attribute group decision making (MAGDM) problem. This paper extends the EDAS method to the 2-tuple linguistic Pythagorean fuzzy sets (2TLPFSs). On the basis of the original EDAS method, 2-tuple linguistic Pythagorean fuzzy EDAS (2TLPF-EDAS) method is built for MAGDM. Finally, a case study for brand packaging design effect evaluation show that the new method proposed in this paper is reasonable.

TODIM-VIKOR method for performance evaluation of school-enterprise cooperation in vocational colleges under 2-tuple linguistic Pythagorean fuzzy sets

As an important way to cultivate talents, school-enterprise cooperation is highly praised by the educational and economic circles of all countries. Vocational education spans enterprises and schools, and is an education of cross-border innovation. Vocational schools should make the people they cultivate meet the needs of the market and enterprises, and carry out in-depth school-enterprise cooperation is one of the effective ways. The school-enterprise cooperation between vocational colleges and enterprises makes vocational education more targeted and practical, and plays an important role in the training of skilled talents. It is not only an inevitable requirement for enterprise development and participation in competition, but also an important direction of China’s vocational education reform, and is the fundamental outlet for the development of China’s vocational education. The performance evaluation of school-enterprise cooperation in 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 2-tuple linguistic Pythagorean fuzzy sets (2TLPFSs) are used as a tool for characterizing uncertain information during the performance evaluation of school-enterprise cooperation in vocational colleges. In this manuscript, we design the 2-tuple linguistic Pythagorean fuzzy TODIM-VIKOR(2TLPF-TODIM-VIKOR) method to solve the MAGDM under 2TLPFSs. In the end, a numerical case study for performance evaluation of school-enterprise cooperation in vocational colleges is given to validate the proposed method.

Spherical fuzzy power partitioned Maclaurin Symmetric Mean Operators and their application in Multiple Attribute Group Decision Making

Spherical fuzzy power partitioned Maclaurin Symmetric Mean Operators and their application in Multiple Attribute Group Decision Making

MABAC framework for logarithmic bipolar fuzzy multiple attribute group decision-making for supplier selection

In this article, we introduce logarithmic operations on bipolar fuzzy numbers (BFNs). We present some new operators based on these operations, namely, the logarithm bipolar fuzzy weighted averaging (L-BFWA) operator, logarithm bipolar fuzzy ordered weighted averaging (L-BFOWA) operator, and logarithm bipolar fuzzy weighted geometric (L-BFWG) operator, and logarithm bipolar fuzzy ordered weighted geometric (L-BFOWG) operator. Further, develop a multi-attribute group decision-making (MAGDM) methodology model based on logarithm bipolar fuzzy weighted averaging operator and logarithm bipolar fuzzy weighted geometric operators. To justify the proposed model’s efficiency, MABAC (the multiple attribute border approximation area comparison) methods are applied to construct MAGDM with BFNs established on proposed operators. To demonstrate the proposed approach’s materiality and efficiency, use the proposed method to solve supply chain management by considering numerical examples for supplier selection. The selection of suppliers is investigated by aggregation operators to verify the MABAC technique. The presented method is likened to some existing accumulation operators to study the feasibility and applicability of the proposed model. We concluded that the proposed model is accurate, effective, and reliable.

Modified GRA method for probabilistic hesitant fuzzy MAGDM and application to network health performance evaluation of radial distribution system

Radial distribution system is an important link connecting power supply and users, and its power supply reliability is directly related to users. Radial distribution network reconfiguration can transform the network structure by changing the switching state of the distribution network lines, and achieve the goals of reducing network operational losses, improving power quality, and power supply reliability while meeting various constraints such as radial operation, power supply and demand balance, capacity, and voltage. Radial distribution systems have the characteristics of multiple components and complex structures. How to quickly and accurately evaluate the health performance of radial distribution systems and find an optimal solution for network reconfiguration are important issues in distribution network analysis. The network health performance evaluation of radial distribution system is classical multiple attributes group decision making (MAGDM). The probabilistic hesitancy fuzzy sets (PHFSs) are used as a tool for characterizing uncertain information during the network health performance evaluation of radial distribution system. In this paper, we extend the classical grey relational analysis (GRA) method to the probabilistic hesitancy fuzzy MAGDM with unknown weight information. Firstly, the basic concept, comparative formula and Hamming distance of PHFSs are briefly introduced. Then, the definition of the score values is employed to compute the attribute weights based on the information entropy method. Then, probabilistic hesitancy fuzzy GRA (PHF-GRA) method is built for MAGDM under PHFSs. Finally, a practical case study for network health performance evaluation of radial distribution system is designed to validate the proposed method and some comparative studies are also designed to verify the applicability.

Extended QUALIFLEX method for MAGDM under Picture 2-Tuple Linguistic environment and applications to college English classroom teaching quality evaluation

With the globalization of the world’s economy, culture, science and technology, and the increasing frequency of international cooperation and exchanges, English will play an increasingly important role. For non-English majors in Chinese colleges and universities, college English is a public compulsory basic course, which plays a very important role in expanding students’ knowledge, improving foreign language cultural literacy and comprehensive language use ability. An important part of college English classroom teaching is teaching evaluation, which not only helps teachers obtain teaching feedback information, improve teaching management, and ensure teaching quality, but also effectively helps students adjust learning strategies, improve learning methods, and improve learning efficiency. The English classroom teaching quality evaluation could be deemed as a classic multiple attribute group decision making (MAGDM) problem. In this paper, as a useful outranking approach, the extended QUALIFLEX method is utilized to address some MAGDM issues by using picture 2-tuple linguistic sets (P2TLSs). In addition, integrating the QUALIFLEX method with P2TLSs, the extended QUALIFLEX method with P2TLNs is constructed and all calculating procedures are simply depicted. Eventually, an empirical application of English classroom teaching quality evaluation has been offered to demonstrate this novel method.

CODAS method for Pythagorean 2-tuple linguistic MAGDM and applications to quality evaluation of scientific research management in application-oriented universities

The scientific research work of colleges and universities has attracted more and more social attention because of its large number of multidisciplinary scientific and technological talents, hardware facilities and good scientific research environment, and the quality of scientific and technological management work of colleges and universities directly affects the level of scientific and technological work of colleges and universities. Starting from the common problems of scientific research management in colleges and universities, this paper explores the ideas and methods to further promote scientific research work by improving the quality of scientific research management. The quality evaluation of scientific research management in application-oriented universities is classical multiple attribute group decision making (MAGDM). Based on this, we extend the traditional CODAS method to the Pythagorean 2-tuple linguistic sets (P2TLSs) and propose the Pythagorean 2-tuple linguistic CODAS (P2TL-CODAS) method for quality evaluation of scientific research management in application-oriented universities. The P2TL-CODAS method is established and all computing steps are simply presented. Furthermore, we apply the P2TL-CODAS method to evaluate the quality evaluation of scientific research management in application-oriented universities.

Sustainable supplier selection by using dual probabilistic linguistic EDAS and ITARA method

With the development of globalization, companies from all over the world are now more closely connected, and they all play different roles in the industry in which they are located. There are more and more companies in a complete supply chain, which can greatly influence the stability of the supply chain, presents certain challenges. Therefore, choosing suppliers with sustainable development capabilities, especially in the event of interruption, can ensure the stability of the entire supply chain, thereby enhancing the company’s image and competitive advantage in a large-scale competition. The sustainable supplier selection is a classical multiple attribute group decision making (MAGDM) issues. In this study, the dual probabilistic linguistic EDAS (DPL-EDAS) method is built based on the traditional EDAS method and dual probabilistic linguistic term sets (DPLTSs). Firstly, the DPLTSs is introduced. Then, combine the traditional EDAS method with DPLTSs information, the DPL-EDAS method is established and the computing steps for MAGDM are built. Finally, there are a numerical case involving sustainable supplier selection and some comparisons in this paper. The comparisons are used to illustrate advantages of DPL-EDAS method.

Research on quality evaluation of industry-education integration for rural vocational education in the perspective of rural revitalization with PL-MACONT method

As one of the teaching models that promote the orderly development of vocational education in China, the integration of industry and education has been recognized by all sectors of society in China’s many years of practice. In recent years, with the strong advocacy of the education sector in China, its development speed has been rapidly improved. Rural vocational education in China has also actively implemented and innovated the teaching mode of integration of industry and education, which has trained more excellent talents for agricultural development in various regions. The quality evaluation of industry-education integration for rural vocational education in the perspective of rural revitalization is viewed as the multiple attribute group decision making (MAGDM). In this paper, the probabilistic linguistic Mixed Aggregation by Comprehensive Normalization Technique (PL-MACONT) method is built for MAGDM. At last, to verify the validity of the extended method, a numerical example to further account for quality evaluation of industry-education integration for rural vocational education in the perspective of rural revitalization is put into use.

An improved CLVA method for evaluating the endurance quality level of young male basketball players with 2-tuple linguistic neutrosophic information

For a long time, the level of endurance quality of our male basketball athletes is not high, and there is a gap with the strongest countries in Europe and America. The former head coach of Chinese men’s basketball team diagnosed the biggest problem of Chinese men’s basketball team and Chinese youth men’s basketball team is the poor quality of endurance. It is especially important to strengthen the endurance training of our basketball players and improve their endurance level. However, from the current situation, the teams in the training due to the lack of standards for endurance quality training has led to a great blindness in endurance quality training. The endurance quality level evaluation of young male basketball players is a classic multiple attribute group decision making (MAGDM) issue with vague, inconsistent, and indeterminate information. The 2-tuple linguistic neutrosophic sets (2TLNSs) is an appropriate form to express the indeterminate decision-making information in the endurance quality level evaluation of young male basketball players. Therefore, in this paper, the 2-tuple linguistic neutrosophic numbers CLVA (2TLNN-CLVA) is built based on traditional close value (CLVA) method and applies it to evaluate the endurance quality level of young male basketball players. Finally, a numerical example for evaluating the endurance quality level of young male basketball players has been given and some decision comparisons are also conducted to further illustrate the advantages of the 2TLNN-CLVA method.

Research and evaluation on comprehensive obstacle-avoiding behavior for unmanned vehicles based on the interval neutrosophic number multiple attribute group decision making

With the advent of the information age, the development direction of automobiles has gradually changed, both from the domestic and foreign policy support attitude, or from the actual actions of the automotive industry and scientific research institutes’ continuous efforts, it is not difficult to see that driverless vehicle. At this time, the testing and evaluation of the intelligent behavior of driverless vehicles is particularly important. It is particularly important not only to regulate the intelligent behavior of unmanned vehicles, but also to promote the key It can not only regulate the intelligent behavior of unmanned vehicles, but also promote the improvement of key technologies of unmanned vehicles and the research and development of driver assistance systems. The evaluation of comprehensive obstacle-avoiding behavior for unmanned vehicles is often considered as a multi-attribute group decision making (MAGDM) problem. In this paper, the EDAS method is extended to the interval neutrosophic sets (INSs) setting to deal with MAGDM and the computational steps for all designs are listed. Then, the criteria importance through intercriteria correlation (CRITIC) is defined to obtain the attribute’s weight. Finally, the evaluation of comprehensive obstacle-avoiding behavior for unmanned vehicles is given to demonstrate the interval neutrosophic number EDAS (INN-EDAS) model and some good comparative analysis is done to demonstrate the advantages of INN-EDAS.

A new method of multi‐attribute group decision making based on hesitant fuzzy soft expert information

AbstractInteresting insights into uncertain multi‐attribute decision‐making systems have come from the theory of hesitant fuzzy sets. Outputs become more reliable when a decision‐maker is not forced to produce one single assessment in the presence of hesitation. Hesitancy in fuzzy environments grants more flexibility to the decision‐maker, therefore enhancing the validity of all subsequent results. Due to these facts, hesitation has become a landmark in the enhancement of fuzzy‐soft‐inspired theories, and techniques using models such as hesitant fuzzy soft sets or hesitant (fuzzy) ‐soft sets have thrived. However, the literature lacks a comparable improvement for fuzzy soft expert information. The main goal of this paper is the integration of both hesitation and fuzziness with the characteristics of soft expert sets. The resulting hybrid model is therefore called hesitant fuzzy soft expert set, and its utilization for multiple attribute group decision‐making (MAGDM) will be investigated too. To that purpose, we first study the required algebraic operations and properties (subsethood and equality, complement, union, intersection, plus AND and OR operation). Respective numerical examples illustrate their utilization. We also establish some important laws for hesitant fuzzy soft expert sets, including commutativity, associativity, distributivity, and De Morgan's laws. Moreover, we define four novel types of level soft expert sets for fuzzy soft expert sets, and three types of fuzzy soft expert sets for hesitant fuzzy soft expert sets, which are: ‐level soft expert sets, level soft expert sets regarding fuzzy threshold, mid‐level soft expert sets and top‐level soft expert sets. Armed with these tools, we present a natural algorithm for MAGDM under hesitant fuzzy soft expert information that is accompanied by an illustrative application that concerns a selection problem for the samples of electric vehicles manufactured by different companies. This is followed by a comparison with existing mathematical tools such as hesitant fuzzy soft sets and fuzzy soft expert sets, in order to show the advantages of our work over them. In the end, we provide some future research directions.

An interaction and feedback mechanism-based group decision-making for emergency medical supplies supplier selection using T-spherical fuzzy information

Selecting a supplier for emergency medical supplies during disasters can be considered a typical multiple attribute group decision-making (MAGDM) problem. MAGDM is an intriguing common problem that is rife with ambiguity and uncertainty. It becomes much more challenging when governments and medical care enterprises adjust their priorities in response to the escalating problems and the effectiveness of the actions taken in different countries. As decision-making problems become increasingly complicated nowadays, a growing number of experts are likely to use T-spherical fuzzy sets (T-SFSs) rather than exact numbers. T-SFS is a novel extension of fuzzy sets that can fully convey ambiguous and complicated information in MAGDM. The objective of this paper is to propose a MAGDM methodology based on interaction and feedback mechanism (IFM) and T-SFS theory. In it, we first introduce T-SF partitioned Bonferroni mean (T-SFPBM) and T-SF weighted partitioned Bonferroni mean (T-SFWPBM) operators to fuse the evaluation information provided by experts. Then, an IFM is designed to achieve a consensus between multiple experts. In the meantime, we also find the weights of experts by using T-SF information. Furthermore, in light of the combination of IFM and T-SFWPBM operator, an MAGDM algorithm is designed. Finally, an example of supplier selection for emergency medical supplies is provided to demonstrate the viability of the suggested approach. The influence of parameters on decision results and comparative analysis with the existing methods confirmed the reliability and accuracy of the suggested approach.

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

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