In this article, we develop the COPRAS model to solve the multiple attribute group decision making (MAGDM) under single-valued neutrosophic 2-tuple linguistic sets (SVN2TLSs). Firstly, we introduce the relevant knowledge about SVN2TLSs in a nutshell, such as the definition, the operation laws, a few of fused operators and so on. Then, combine the traditional COPRAS model with SVN2TLNs, and structure as well as elucidate the computing steps of the SVN2TLNCOPRAS pattern. Furthermore, in this article, we propose a method for determining attribute weights in different situations relying on the maximizing deviation method with SVN2TLNs. Last but not least, a numerical example about assessing the safety of construction project has been designed. And for further demonstrating the advantage of the new designed method, we also select a number of existed methods to have comparisons.
On the basis of previous scholars’ research, we improve the traditional TOmada de Decisão Interativa e Multicritério (TODIM) along with Cumulative Prospect Theory (CPT) under the 2‐tuple linguistic Pythagorean fuzzy sets (2TLPFSs) in this article. First of all, we give some definitions of Pythagorean fuzzy sets, 2TLPFSs, and the 2‐tuple linguistic Pythagorean fuzzy weighted average as well as 2‐tuple linguistic Pythagorean fuzzy weighted geometric operators. After that, according to the existing researches, we simply introduce the TODIM method and TODIM method under 2TLPFSs. Furthermore, we propose the TODIM method based on CPT (CPT–TODIM) for multiple attribute group decision‐making (MAGDM) with 2TLPFSs. Finally, a numerical example about company credit risk assessment is used to explain the new proposed method. Comparing with other methods, there is no doubt that this new method has superiority. To be exact, because the new method fully considers the mental factors of decision makers, it can better solve the uncertainty of MAGDM and improve the rationality of decision‐making.
Since people around the world have gradually attached importance to resource conservation, various countries are actively taking measures to promote environmental protection and sustainable development. Green supply chain management (GSCM) have emerged in this context. Thus, in this essay, a novel intuitionistic fuzzy multiple attribute group decision making (MAGDM) method is designed to tackle this issue. First of all, CRITIC (Criteria Importance Through Inter-criteria Correlation) method is utilized to determine the weights of criteria. Later, the conventional Taxonomy method is extended to the intuitionistic fuzzy environment to compute the value of development attribute of each supplier. Then, the optimal one can be determined. Eventually, an application about green supplier selection in steel industry is presented, and a comparative analysis is made to demonstrate the superiority of the proposed method. The main features of the proposed algorithm are that they provide a practical solution for selecting GSCM and presents an objective weighting method to enhance the effectiveness of the algorithm.
The 2-tuple linguistic neutrosophic set (2TLNS) does a good job in coping with vague and uncertain environments and has been widely used in numerous fields. In this article, we come up with a new solution of mul
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