The cache replacement policy (CRP) can reduce cache redundancy, improve cache usefulness, and increase network efficiency in content-centric networks (CCN). The essential challenges in addressing CRP in (CCN) evaluation involve significant fuzziness. As a result, CRP evaluation is important. A more effective way to capture fuzziness is the spherical fuzzy rough set (SFRS). The purpose of this paper is to focus on multi-criteria group decision making (MCGDM) using SFR settings and new SFR Einstein geometric aggregation operators. The basic principles of the aggregation operator are clearly discussed. MCGDMs was developed by proposed method. SFR-EDAS model and its stepwise algorithm is given. The effectiveness of the proposed method was empirically performed by cache replacement policy example and compared with EDAS method.

Branded apps offer both an essential tool for businesses and consumers to interact in real-time and share marketing messages as well as an innovative approach to business that promotes value co-creation. In order to explore the impact of branded apps on customers, this study provides a Three-way decision (TWDs) technique with decision-theoretic rough sets (DTRSs) for selecting branded apps under spherical double hierarchy linguistic term sets (SDHLTSs) information. SDHLTSs is a combination of the first hierarchy linguistic term and the second hierarchy linguistic term that can more flexibly describe ambiguity and uncertainty in decision-making (DM) problems. To aggregate the SDHLTSs, we propose a series of aggregation operators and fundamental operational laws for SDHLTSs. A grey relational analysis is considered to evaluate a conditional probability, which improves decision-making. A step-wise algorithm of the TWDs method based on decision-theoretic rough sets (DTRSs) is given for SDHLTSs. Further, a proposed aggregation operator is used to compute the loss function, and the decision’s results are decided by the minimum-loss principle. Finally, a real-world case study of the brand experience of a branded app is considered to demonstrate the efficiency of the proposed methods.

The demand for third-party logistics (3PL) providers becomes an increasingly important issue for corporations seeking improved customer service and cost reduction. Currently, there is no way to select the appropriate method for selecting 3PL. Therefore, this paper develops a new extended multi-objective optimization ratio analysis plus full multiplicative form (MULTIMOORA) method under double hierarchy linguistic single-valued neutrosophic sets (DHLSVNSs). For this, we first develop a new mathematical tool, i.e., DHLSVNSs, by studying single-valued neutrosophic set (SVN) and double hierarchy linguistic term set (DHLTSs), which is very effective for solving uncertainty in decision-making problems. A list of Einstein aggregation operators and their fundamental aspects for DHLSVNSs are presented based on Einstein's norms, as aggregation operators play an essential role in decision-making. A step-by-step algorithm of the Extended DHLSVN-MULTIMOORA approach is designed to tackle ambiguous and uncertain data during decision-making problems. The algorithm developed for the suggested technique is illustrated with a numerical example relevant to 3PL. A comparison of the proposed methods with various existing methodologies is carried out to demonstrate the superiority of the suggested algorithms.

In this article, we shall introduce a novel technique for order preference by similarity to ideal solution (TOPSIS)-based methodology to resolve multicriteria group decision-making problems within picture fuzzy environment, where the weights information of both the decision makers (DMs) and criteria are completely unknown. First, we briefly review the definition of picture fuzzy sets (PFS), score function and accuracy function of PFRSs and their basic operational laws. In addition, defined the generalized distance measure for PFRSs based on picture fuzzy rough entropy measure to compute the unknown weights information. Secondly, the picture fuzzy information based decision-making technique for multiple attribute group decision making (MAGDM) is established and all computing steps are simply depicted. In our presented model, it's more accuracy and effective for considering the conflicting attributes. Finally, an illustrative example with robot selection is provided to demonstrate the effectiveness of the proposed picture fuzzy decision support approaches, together with comparison results discussion, proving that its results are feasible and credible.