Multiple‐attribute group decision‐making method of linguisticq‐rung orthopair fuzzy power Muirhead mean operators based on entropy weight

Incomplete linguistic q-rung orthopair fuzzy preference relations and their application to multi-criteria decision making

With the development of social and economic research, the judgements that people deal with are full of fuzziness and vagueness. It is convenient to use the linguistic q-rung orthopair fuzzy numbers to offer the qualitative uncertain information. Consequently, in this paper, we mainly study linguistic q-rung orthopair fuzzy preference relations (Lq-ROFPRs) and apply them to a multi-criteria decision-making (MCDM) problem. The multiplicative consistency of Lq-ROFPRs is first introduced, then a consistency-based model is established to derive the normalized linguistic q-rung orthopair fuzzy priority weight vector. The concept of acceptably multiplicative consistency is further defined, and an optimization model is formulated to repair the unacceptably multiplicative consistent Lq-ROFPR. To cope with the incomplete Lq-ROFPR, another programming model is built to ascertain the missing values. The weights of criteria are determined by constructing a possibility degree matrix. Subsequently, an MCDM problem with incomplete Lq-ROFPRs is considered and a step-by-step algorithm is put forward. Finally, the proposed method is applied to three examples, and the advantages of this new approach are also demonstrated.

WDBA method for probabilistic linguistic MAGDM with entropy weight and application to consumer competitiveness evaluation in creative and cultural industries

With the steady development of China’s economy, under the new economic normal, the creative cultural industry has been continuously optimized and developed in terms of structure, scale and quality, and the connotation of the creative cultural industry has been continuously enriched, forming a three-dimensional and diversified pattern. With the help of high-tech, culture, multimedia and other means, the current creative cultural industry is continuously absorbing and integrating it on a large scale, promoting the optimization, upgrading and innovative development of the industry. The consumer competitiveness evaluation in creative and cultural industries is a classical MAGDM problems. In this paper, WDBA method is designed for solving the probabilistic linguistic MAGDM(PL-MAGDM) with the completely unknown weights. In the end, an empirical application for consumer competitiveness evaluation in creative and cultural industries is used to demonstrate the use of the developed method. The proposed method can also contribute to the selection of suitable alternative successfully in other selection problems.

Linguistic q-rung orthopair fuzzy multiple-attribute group decision making based on the grey similarity degree and PROMETHEE II method

Linguistic q-rung orthopair fuzzy numbers (Lq-ROFNs) are an effective tool for representing fuzzy linguistic information, and they can obtain a wider expression scope than linguistic intuitionistic fuzzy numbers and linguistic Pythagorean fuzzy numbers by increasing the value of parameter q. In this paper, we propose a new similarity measure called the grey similarity degree between any two Lq-ROFNs based on the concept of the grey correlation degree. Considering the significance of determining unknown weights, we also propose a grey correlation method to determine each expert’s weight under different alternatives and attributes, and we construct an optimization model to determine incompletely known attribute weights. Furthermore, an approach to linguistic q-rung orthopair fuzzy multiple-attribute group decision making is proposed that combines the grey similarity degree with the PROMETHEE II method. Finally, a numerical example is given to illustrate the effectiveness of the proposed method, and a sensitivity analysis and comparison analysis are also performed.

Interval-valued intuitionistic pure linguistic entropy weight method and its application to group decision-making

In recent years, the problem of complex multi-attribute group decision-making (MAGDM) in uncertain environments has received increasing attention. In evaluating MAGDM problems, obtaining the objective attribute weights is very important. Considering the excellent performance of intuitive fuzzy linguistic sets in dealing with uncertain information, this paper introduces a new interval-valued intuitionistic pure linguistic entropy weight (IVIPLEW) method for determining attribute weights and evaluating MAGDM problems. The IVIPLEW method considers the cases of missing values, and uses the conventional interval-valued intuitionistic pure linguistic (IVIPL) expectations to supplement the missing values. This method of dealing with missing values not only considers the expectations of experts, but also prevents fluctuations in linguistic variables from impacting the decision results. This paper establishes an analysis framework that allows the IVIPLEW method to be applied to MAGDM problems, and presents a practical case study that illustrates the practicality and effectiveness of IVIPLEW. The results are quite satisfactory. The effectiveness of the proposed method is demonstrated through a comparison with the IVIPL information aggregation method. Furthermore, the robustness of the IVIPLEW method is verified through a sensitivity analysis. The results presented in this paper show that the IVIPLEW method is applicable to a wide range of MAGDM problems.

Sustainable Higher Education Reform Quality Assessment Using SWOT Analysis with Integration of AHP and Entropy Models: A Case Study of Morocco

Sustainable development goals (SDG) involve not only environmental issues but also economic, social, and cultural concerns. Higher education plays a key role in promoting sustainable development initiatives and in empowering people to change their thinking and to strive for a sustainable future. However, the main issue that needs to be presently resolved is how leaders, teachers, and students in higher education can achieve sustainable development in their system vision, mission and values, strategic plans, and organizational culture. Morocco is a country with a long history of higher education and has continuous reforms for sustainable development. In the process of responding to the wave of globalization, the Moroccan government has begun to formulate a higher education reform plan to maintain its competitiveness and achieve the SDG standards. Therefore, this study is focused on the quality of the higher education system through which the sustainability of higher education reform can be implemented. With this in mind, an organized approach that involved a questionnaire using the SWOT (strengths, weaknesses, opportunities, and threats) decision-making model with integration of analytic hierarchy process (AHP) and Entropy method was developed. The questionnaires were filled out by the experts, staff, and students of the higher education system (universities) to obtain the important key factors for the SWOT analysis. The AHP was used for the qualitative analysis of the weights of the SWOT factors, while the Entropy method was applied for the objective analysis of the number of different weight attributes. After integration of AHP with Entropy, the finalized variables were ranked; these results are more reliable and realistic to decision-makers. Finally, the SWOT matrix was established based on the questionnaire assessment and the AHP with Entropy weights to help implement the higher education reform policy and to monitor the quality of the current education system. The results also indicate that higher education reform must incorporate many changes, including effective budget planning, skilled experts, internationalization, improved and expanded infrastructure, reformed study curriculum, and latest training.

Multi-attribute group decision making based on sine trigonometric spherical fuzzy aggregation operators

Spherical fuzzy set (SFS) is also one of the fundamental concepts for address more uncertainties in decision problems than the existing structures of fuzzy sets, and thus its implementation was more substantial. The well-known sine trigonometric function maintains the periodicity and symmetry of the origin in nature and thus satisfies the expectations of the experts over the multi parameters. Taking this feature and the significance of the SFSs into the consideration, the main objective of the article is to describe some reliable sine trigonometric laws for SFSs. Associated with these laws, we develop new average and geometric aggregation operators to aggregate the Spherical fuzzy numbers. Then, we presented a group decision-making strategy to address the multi-attribute group decision-making problem using the developed aggregation operators. To verify the value of the defined operators, a MAGDM strategy is provided along with an application for the selection of an authentic COVID-19 laboratory. Moreover, a comparative study is also performed to present the effectiveness of the developed approach.

Generalized complex q-rung orthopair fuzzy Einstein averaging aggregation operators and their application in multi-attribute decision making

The recently proposed q-rung orthopair fuzzy set, which is characterized by a membership degree and a non-membership degree, is effective for handling uncertainty and vagueness. This paper proposes the concept of complex q-rung orthopair fuzzy sets (Cq-ROFS) and their operational laws. A multi-attribute decision making (MADM) method with complex q-rung orthopair fuzzy information is investigated. To aggregate complex q-rung orthopair fuzzy numbers, we extend the Einstein operations to Cq-ROFSs and propose a family of complex q-rung orthopair fuzzy Einstein averaging operators, such as the complex q-rung orthopair fuzzy Einstein weighted averaging operator, the complex q-rung orthopair fuzzy Einstein ordered weighted averaging operator, the generalized complex q-rung orthopair fuzzy Einstein weighted averaging operator, and the generalized complex q-rung orthopair fuzzy Einstein ordered weighted averaging operator. Desirable properties and special cases of the introduced operators are discussed. Further, we develop a novel MADM approach based on the proposed operators in a complex q-rung orthopair fuzzy context. Numerical examples are provided to demonstrate the effectiveness and superiority of the proposed method through a detailed comparison with existing methods.

Q-Rung Probabilistic Dual Hesitant Fuzzy Sets and Their Application in Multi-Attribute Decision-Making

The probabilistic dual hesitant fuzzy sets (PDHFSs), which are able to consider multiple membership and non-membership degrees as well as their probabilistic information, provide decision experts a flexible manner to evaluate attribute values in complicated realistic multi-attribute decision-making (MADM) situations. However, recently developed MADM approaches on the basis of PDHFSs still have a number of shortcomings in both evaluation information expression and attribute values integration. Hence, our aim is to evade these drawbacks by proposing a new decision-making method. To realize this purpose, first of all a new fuzzy information representation manner is introduced, called q-rung probabilistic dual hesitant fuzzy sets (q-RPDHFSs), by capturing the probability of each element in q-rung dual hesitant fuzzy sets. The most attractive character of q-RPDHFSs is that they give decision experts incomparable degree of freedom so that attribute values of each alternative can be appropriately depicted. To make the utilization of q-RPDHFSs more convenient, we continue to introduce basic operational rules, comparison method and distance measure of q-RPDHFSs. When considering to integrate attribute values in q-rung probabilistic dual hesitant fuzzy MADM problems, we propose a series of novel operators based on the power average and Muirhead mean. As displayed in the main text, the new operators exhibit good performance and high efficiency in information fusion process. At last, a new MADM method with q-RPDHFSs and its main steps are demonstrated in detail. Its performance in resolving practical decision-making situations is studied by examples analysis.

Refined Expected Value Decision Rules under Orthopair Fuzzy Environment

Refined expected value decision rules can refine the calculation of the expected value and make decisions by estimating the expected values of different alternatives, which use many theories, such as Choquet integral, PM function, measure and so on. However, the refined expected value decision rules have not been applied to the orthopair fuzzy environment yet. To address this issue, in this paper we propose the refined expected value decision rules under the orthopair fuzzy environment, which can apply the refined expected value decision rules on the issues of decision making that is described in the orthopair fuzzy environment. Numerical examples were applied to verify the availability and flexibility of the new refined expected value decision rules model. The experimental results demonstrate that the proposed model can apply refined expected value decision rules in the orthopair fuzzy environment and solve the decision making issues with the orthopair fuzzy environment successfully.

Dombi power partitioned Heronian mean operators of q-rung orthopair fuzzy numbers for multiple attribute group decision making

In this paper, a set of Dombi power partitioned Heronian mean operators of q-rung orthopair fuzzy numbers (qROFNs) are presented, and a multiple attribute group decision making (MAGDM) method based on these operators is proposed. First, the operational rules of qROFNs based on the Dombi t-conorm and t-norm are introduced. A q-rung orthopair fuzzy Dombi partitioned Heronian mean (qROFDPHM) operator and its weighted form are then established in accordance with these rules. To reduce the negative effect of unreasonable attribute values on the aggregation results of these operators, a q-rung orthopair fuzzy Dombi power partitioned Heronian mean operator and its weighted form are constructed by combining qROFDPHM operator with the power average operator. A method to solve MAGDM problems based on qROFNs and the constructed operators is designed. Finally, a practical example is described, and experiments and comparisons are performed to demonstrate the feasibility and effectiveness of the proposed method. The demonstration results show that the method is feasible, effective, and flexible; has satisfying expressiveness; and can consider all the interrelationships among different attributes and reduce the negative influence of biased attribute values.