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The evaluation of employment quality in higher education institutions refers to assessing graduates' performance and employment status through multiple dimensions. It mainly includes employment rate, job satisfaction, salary levels, industry distribution, and career development prospects. This evaluation not only reflects the educational quality and social recognition of the institution but also provides valuable insights for optimizing teaching and training programs, helping graduates better meet the demands of the labor market. The employment quality evaluation in higher education institutions is a multi-attribute group decision-making (MAGDM) problem. Recently, the Exponential TODIM (ExpTODIM) and VIKOR methods have been applied to address MAGDM challenges. Singlevalued neutrosophic sets (SVNSs) are employed as a tool to represent uncertain data in the employment quality evaluation in higher education institutions. In this paper, we propose the singlevalued neutrosophic number Exponential TODIM-VIKOR (SVNN-ExpTODIM-VIKOR) method to solve MAGDM problems under SVNSs. Finally, a numerical case study is presented to validate the effectiveness of the proposed method in evaluating the employment quality in higher education institutions. [ABSTRACT FROM AUTHOR]

Under the background of big data, the evaluation of college students' satisfaction with online ideological and political education (IAPE) is primarily achieved through data mining and analysis techniques, allowing for a more comprehensive and accurate reflection of students' attitudes and feedback. By collecting data through online surveys, social media interactions, and other channels, educators can adjust the content and methods of teaching in real-time to better meet students' needs and improve the effectiveness and satisfaction of IAPE. The satisfaction evaluation of college students' online IAPE in the context of big data is a multiattribute group decision-making (MAGDM) problem. Recently, VIKOR method have been applied to address MAGDM challenges. Single-valued neutrosophic sets (SVNSs) are employed as a tool to represent uncertain data in the satisfaction evaluation of college students' online IAPE within the big data context. In this paper, we propose the single-valued neutrosophic number VIKOR (SVNN-VIKOR) method to solve MAGDM problems under SVNSs. Finally, a numerical case study is presented to validate the effectiveness of the proposed method in evaluating the satisfaction of college students' online IAPE in the context of big data. [ABSTRACT FROM AUTHOR]

University educational management quality evaluation is a systematic assessment of various elements involved in the educational management process of higher education institutions. Its goal is to analyze aspects such as management systems, resource allocation, faculty quality, student services, and curriculum design, measuring the impact of management practices on teaching outcomes to ensure educational objectives are met. This evaluation system helps improve the operational efficiency and teaching quality of universities, enhancing their reputation and aligning talent cultivation with societal needs. The quality evaluation of university educational management is a task well-suited for multi-attribute group decision-making (MAGDM). Recently, the Exponential TODIM (ExpTODIM) and VIKOR methods have been introduced to address MAGDM challenges. For handling uncertain data during this evaluation, the 2-tuple linguistic neutrosophic sets (2TLNSs) have been introduced as an effective tool. In this research, the 2-tuple linguistic neutrosophic number ExpTODIM-VIKOR (2TLNN-ExpTODIM-VIKOR) method is introduced to tackle MAGDM challenges using 2TLNSs. Furthermore, a numerical study focusing on the quality evaluation of university educational management is conducted to validate the effectiveness of the 2TLNN-ExpTODIM-VIKOR approach. [ABSTRACT FROM AUTHOR]

The construction of sponge city (SC) public private partnership (PPP) projects is considered to be a feasible measure to solve the "water problems" in China. To ensure the success of SC PPP projects, how to select an appropriate operation mode for SC PPP projects is an urgent problem to be solved. In this paper, first, the evaluation index system of operation mode is established from the aspects of project characteristics, government capabilities, project benefits, project implementation, and cooperative partnership. Second, the DEMATEL method and entropy method are introduced to overcome the drawbacks of a single method, and the combination weights are calculated by game theory. Finally, the decision-making model based on intuitionistic fuzzy soft set (IFSS)-prospect theory and VIKOR approach is constructed to select operation mode for SC PPP projects. In this paper, the framework is applied to select an operation mode for the Qingshan demonstration zone project, and its feasibility and effectiveness are verified through sensitivity analysis and comparative analysis. The results show that BOT is the optimal operation mode for SC PPP projects, and government capabilities and project implementation are critical factors to be considered when selecting an operation mode. This study can provide guidance to the government in the OMS of SC PPP projects and improve the sustainability of the projects. [ABSTRACT FROM AUTHOR]

Network slicing in 5G is expected to essentially change the way in which network operators deploy and manage vertical services with different performance requirements. Efficient and secure slice provisioning algorithms are important since network slices share the limited resources of the physical network. In this article, we first analyze the security issues in network slicing and formulate an Integer Linear Programming (ILP) model for secure 5G core network slice provisioning. Then, we propose a heuristic 5G core network slice provisioning algorithm called VIKOR-CNSP based on VIKOR, which is a multi-criteria decision making (MCDM) method. In the slice node provisioning stage, the node importance is ranked with the VIKOR approach by considering the node resource and topology attributes. The slice nodes are then provisioned according to the ranking results. In the slice link provisioning stage, the k shortest path algorithm is implemented to obtain the candidate physical paths for the slice link, and a strategy for selecting a candidate physical path is proposed to increase the slice acceptance ratio. The strategy first calculates the path factor Pf which is the product of the maximum link bandwidth utilization of the candidate physical path and its hop-count, and then chooses the candidate physical path with the smallest Pf to host the slice link. Extensive simulations show that the proposed algorithm can achieve the highest slice acceptance ratio and the largest provisioning revenue-to-cost ratio, satisfying the security constraints of 5G core network slice requests.

In many practical applications, we have several different criteria for making a decision. In such situations, we need to take all these criteria into account. One of the most widely used approaches for solving such multi-criteria decision making problems was proposed in 1979 by S. Opricovic; it is known as VIKOR. This approach has been widely and successfully used—to the extent that the corresponding 2004 paper became, in 2009, the most cited paper in the field of economics. However, this approach is largely empirical; as a result, it is not clear why this approach has been so successful. In this paper, we provide theoretical justifications for the VIKOR approach and thus explain its empirical success. [ABSTRACT FROM AUTHOR]

Product service system (PSS) is an important strategy for manufacturing companies to improve competitiveness. The extension of supply range forces the manufacturing companies to select service suppliers to support PSS development due to the constraint of resources and capability. VIKOR approach is applied to evaluate the service suppliers based on compromise programming. To deal with the uncertain evaluation information, evaluation data are expressed as vague values by means of vague set theory. In the vague VIKOR, the maximised group utility and minimised individual regret are obtained based on similarity measure between two vague values. A set of criteria weights is a critical input of VIKOR. The traditional weights-determining approaches are subjective and have higher uncertainty such as analytic hierarchy process and analytic network process. Rough set mining approach can be used to obtain the criteria weights according to the surveyed performance information on each criterion and on the whole. The traditional rough set has poor noise-tolerance capability, the variable precision rough set approach is used to mine the criteria weights, and a mining algorithm is proposed in this paper. A case study of rescue service supplier evaluation in excavator PSS development is presented to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Assigning precise values for attributes in most engineering applications is almost impossible. It is therefore necessary to consider yarn properties as intervals. Hence, an extended version of VIKOR was employed in this study to select suitable spinning conditions for the weft knitting process among feasible alternatives. Three variables in rotor-spun box were considered and their performances were evaluated based on seven quality parameters using 16 yarn samples. The final ranking was presented according to the relative closeness coefficient of the ideal solution. Consequently, stability of the proposed final ranking was verified. [ABSTRACT FROM AUTHOR]