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The high-speed train (HST) system is one of the most critical components of national and international passenger transportation networks. Selecting the appropriate train sets is a critical task for railway operators to build an efficient, productive, safe, inexpensive and environmentally friendly passenger transport network system. On the other hand, selecting the proper HST set is a highly complex process since many conflicting criteria, and decision alternatives make it difficult for decision-makers. This paper suggests the fuzzy Grey Relational Analysis technique. In addition, the fuzzy technique proposed in the current paper has been implemented in two ways: using both the experts' linguistic evaluations and crisp numbers to compare real numerical values and fuzzy evaluations. A comprehensive sensitivity analysis was then conducted to assess the validation of the proposed fuzzy technique and its results in applying this method. The decision alternative of A8 Siemens is the best option for all scenarios, and it has been observed that there are slight differences, which cannot change the overall result in the ranking positions of the options. The analysis results prove that the fuzzy method can be applied to solve these complicated decision-making problems and that the obtained results are robust, accurate, applicable, and realistic. [ABSTRACT FROM AUTHOR]

The competition between real estate enterprises in the future is likely to be between supply chains, and strategic general contracting is an important part. Implementing strategic construction general contracting procurement is beneficial for improving procurement efficiency and transparency, saving procurement costs, improving procurement quality, achieving economies of scale, and opening up or enhancing the core competitiveness of real estate enterprises. It has practical and guiding significance for the long-term and good development of real estate enterprises. The capability evaluation of real estate general contractors is a multiple-attribute decision-making (MADM) problem. Recently, the Exponential TODIM(ExpTODIM) and (grey relational analysis) GRA technique has been used to cope with MADM issue. The hesitant triangular fuzzy sets (HTFSs) are used as a tool for characterizing uncertain information during the capability evaluation of real estate general contractors. In this paper, the hesitant triangular fuzzy Exponential TODIM-GRA (HTF-ExpTODIM-GRA) technique is built to solve the MADM under HTFSs. In the end, a numerical case study for capability evaluation of real estate general contractors and some comparative analysis is given to validate the proposed technique. The main contribution of this paper is managed: (1) The MEREC technique is constructed to obtain weight values under HTFSs; (2) an integrated HTF-ExpTODIM-GRA technique is constructed to manage the MADM issue; (3) An illustrative example for capability evaluation of real estate general contractors has accomplished to verify the HTF-ExpTODIM-GRA technique. [ABSTRACT FROM AUTHOR]

Interval-valued q-rung orthopair fuzzy numbers (IVq-ROFNs), as a generalization of the q-rung orthopair fuzzy numbers, are a more robust and reliable tool when dealing with uncertain information during decision-making processes, and can therefore be applied to a broader range of situations. This paper presents an approach to a multi-attribute group decision-making (MAGDM) problem in an IVq-ROF environment. In decision-making, the most sensitive part is information fusion (information aggregation); for this purpose, we extend the Einstein geometric aggregation operator for IVq-ROFNs. Einstein operators are valuable in information fusion, as they consider the interrelationship between arguments. Thus, while dealing with the information fusion process, the interrelationship between arguments ensures that aggregated values do not lose information. We use the traditional grey relational analysis (GRA) approach to rank the alternatives based on the attributes. In the GRA approach, we use positive and negative ideal solutions to obtain the grey relational coefficient (GRC). The GRCs of alternatives are calculated based on a new distance measure, which utilizes the hesitancy or indeterminacy degree of IVq-ROFNs. Utilizing the hesitancy or indeterminacy degree in distance measures reduces information loss significantly. The proposed approach considers three cases of attributes' weights: partially known, completely unknown, and known. Consideration of three cases of attributes' weights allows the approach to be applied to any appropriate MAGDM problem. We establish an optimization model to compute partially known attributes' weights; we use the entropy weight determination method to compute unknown attributes' weights. Finally, we discuss a real-world case study to validate the proposed approach. [ABSTRACT FROM AUTHOR]

Over two decades, telecommunication market has been continuing a huge growth in urban, semi-urban and rural regions of India. Investigating and choosing the desirable cellular mobile telephone service providers (TSPs) based on operative constraint can facilitate to obtain the ideal of TSPs selection. Here, the evaluation commonly encompasses different TSP options under various operational factors; thus, the assessment of TSPs can be considered as a rigorous multi-criteria decision-making (MCDM) issue. This paper initiates a structure for the exploration of the TSPs in the Madhya Pradesh region, India. To do this, a framework associated with grey relational analysis (GRA) on intuitionistic fuzzy sets (IFSs) is planned to obtain the performance of various telecom participants. The developed approach is based on the conception of the best and worst solutions. To find the attribute weights, a divergence measure is developed and employed by relative comparisons. Additionally, to show the proficiency and practicality, a selection problem of TSPs options of Madhya Pradesh circle, India is presented within the IFSs context. By employing the developed model, an expert can enlarge tactics to enhance the performance by standard operational factors. Comparison and sensitivity analysis are considered to validate the developed approach in the prioritization of the TSPs options. [ABSTRACT FROM AUTHOR]

With the increasing number of students majoring in art in universities, the improvement of the quality of art teaching in universities is becoming increasingly important. However, due to the unique characteristics of art teaching compared to other majors, in order to improve the quality of art teaching, it is necessary to follow the individual characteristics of art majors and students, and establish corresponding systems to ensure the steady improvement of teaching quality, while taking students as the main body. Thus, the overall quality of cultivating art talents in universities can be improved. The art education quality evaluation in higher education institutions is MAGDM. In recent years, the Exponential TODIM (ExpTODIM) and grey relational analysis (GRA) technique was employed to deal with MAGDM. The 2-tuple linguistic Pythagorean fuzzy sets (2TLPFSs) are employed as an effective tool for expressing uncertain decision information during the art teaching quality evaluation in higher education institutions. In this paper, the 2-tuple linguistic Pythagorean fuzzy number Exponential TODIM-GRA (2TLPFN-ExpTODIM-GRA) technique is implemented to deal with MAGDM under 2TLPFNs. Finally, a numerical example for art teaching quality evaluation in higher education institutions is implemented to verify the proposed technique. The research contributions of this work are outlined: (1) the entropy technique is employed to conduct the attribute’s weight; (2) the 2TLPFN-ExpTODIM-GRA technique is implemented to implement the MAGDM under 2TLPFNs; (3) a numerical example for art teaching quality evaluation in higher education institutions and several comparative analysis is employed to validate the 2TLPFN-ExpTODIM-GRA technique. [ABSTRACT FROM AUTHOR]

To offer better treatment for a COVID-19 patient, preferable medicine selection has become a challenging task for most of the medical practitioners as there is no such proven information regarding it. This article proposes a decision-making approach for preferable medicine selection using picture fuzzy set (PFS), Dempster–Shafer (D–S) theory of evidence and grey relational analysis (GRA). PFS is an extended version of the intuitionistic fuzzy set, where in addition to membership and non-membership grade, neutral and refusal membership grades are used to solve uncertain real-life problems more efficiently. Hence, we attempt to use it in this article to solve the mentioned problem. Previously, researchers considered the neutral membership grade of the PFS similar to the other two membership values (positive and negative) as applied to the decision-making method. In this study, we explore that neutral membership grade can be associated with probabilistic uncertainty which is measured using D–S theory of evidence and FUSH operation is applied for the aggregation purpose. Then GRA is used to measure the performance among the set of parameters which are in conflict and contradiction with each other. In this process, we propose an alternative group decision-making approach by the evidence of the neutral membership grade which is measured by the D–S theory and the conflict and contradiction among the criteria are managed by GRA. Finally, the proposed approach is demonstrated to solve the COVID-19 medicine selection problem. [ABSTRACT FROM AUTHOR]