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Spherical fuzzy soft expert set (SFSES) theory blends the perks of spherical fuzzy sets and group decision-making into a unified approach. It allows solutions to highly complicated uncertainties and ambiguities under the unbiased supervision and group decision-making of multiple experts. However, SFSES theory has some deficiencies such as the inability to interpret and portray the bipolarity of decision-parameters. This work highlights and overcomes these limitations by introducing the novel spherical fuzzy bipolar soft expert sets (SFBSESs) as a powerful hybridization of spherical fuzzy set theory with bipolar soft expert sets (BSESs). Followed by the development of certain set-theoretic operations and properties of the proposed model, important problems, including the selection of non-powered dam (NPD) sites for hydropower conversion are discussed and solved under the proposed approach. These problems mainly focus on the need for an efficient tool capable of considering the bipolarity of parameters, complicated ambiguities, and multiple opinions. Supporting the new approach by a detailed comparative analysis, it is concluded that the proposed model is more comprehensive and reliable for multi-attribute group decision-making (MAGDM) than the previous tools, particularly considering the bipolarity of parameters under SFSES environment. [ABSTRACT FROM AUTHOR]

In this paper, we set forth a framework for solving a multiattribute group decision-making (MAGDM) problem, namely, the selection of a firm for participation in a Saudi oil refinery project in Pakistan. This project will prove a key success factor for the economic growth of Pakistan due to its enormous economic impact on the energy sector, industrial development, commerce, transportation, and so on. This multiplicity justifies that several intricate components comprising both intrinsic and external attributes should be adequately evaluated for the selection of such a firm, that is, the formulation of this question as a MAGDM problem. Nonbinary evaluation with two-dimensional ambiguity and uncertainty in the parameters are general concerns in modern literature, and they fit into this problem. Within this context, one of the most superior and amenable theories (complex spherical fuzzy N -soft sets, henceforth C S F N S f S s) shall be used to formulate a new comprehensive method, known as complex spherical fuzzy N -soft-VIKOR (C S F N S f -VIKOR) method. According to the general spirit of the benchmark technique, the normalized Euclidean distances and the weights of the attributes are jointly handled, and as consequence, two main features ("maximum group utility" and "minimum individual regret") are acquired. The coefficient strategy with reference to group utility measure and individual regret measure of opponents are employed for the compromise measure. Armed with this novel tool, we single out the most feasible firm according to the preference order of the alternatives examined by the decision-makers on the subject of linear normalized weights of experts and attributes. Furthermore, a comparative analysis justifies the C S F -VIKOR method, and some results prove its capabilities and validity. Moreover, a sensitivity test certifies the stability of the proposed method. [ABSTRACT FROM AUTHOR]

Multi-attribute group decision-making (MAGDM) phenomenon is used to handle the information, when a number of attributes of alternatives are evaluated by a group of decision-makers. In this research article, we develop a novel approach called interval-valued hesitant fuzzy N-soft sets (IVHFNSSs) and extend the method of TOPSIS for solving MAGDM problems. In our proposed model, the evaluation information provided by the decision-makers is expressed in the form of ratings, grades and IVHFEs, whereas the information about attribute weights is arbitrary. The model provides us information about the occurrence of ratings or grades in hesitant situation. Moreover, we investigate some useful properties of IVHFNSSs and construct fundamental operations on them. By using the extended TOPSIS method, we describe potential applications of IVHFNSSs in MAGDM. We present our method in an algorithm and a graphical structure. [ABSTRACT FROM AUTHOR]

In this article, we apply the concept of m-polar fuzzy sets in labeling graphs and introduce the concept of m-polar fuzzy labeling graphs. We present properties of m-polar fuzzy labeling cycle and m-polar fuzzy labeling with bridge and cut nodes. We introduce several different types of distances, including w-distance, strongest strong distance, strong geodesic distance, $$\delta $$ -distance in m-polar fuzzy labeling graph and investigate some of their properties. We also present an application of m-polar fuzzy labeling graphs in image processing. [ABSTRACT FROM AUTHOR]