# A VIKOR-Based Sequential Three-Way Classification Ranking Method
At the same time, some studies have pointed out that the traditional MCDM method can only rank schemes, but not classify them. [PERSON] et al. [6] saw unity in multi-attribute and three-way decisions as a viable research path, proposing a new TOPSIS method based on three-way decisions. [PERSON] et al. [7] also believed that three-way decision making increases delayed decision and can efficiently cope with multi-attribute decision making by reducing decision risk. Therefore, the VIKOR method can be considered to combine with the three-way decisions to take into account both classification and ranking. Based on human cognitive processes, a three-way decision model is constructed. People often put off making decisions that require deliberation. Three-way decisions solve complex problems by dealing with three different parts, so that the VIKOR method can deal with decision complexity, consider cost and uncertainty, and complete classification and ranking. [PERSON] et al. [8] proposed a three-way decision model on account of the third-generation prospect theory, introduced the \(\alpha\) model and \(\beta\) model optimization of digital threshold solution, and simplified the three-way decision rules. [PERSON] et al. [9] generalize the related work of three-way decisions through complex network analysis. [PERSON] et al. [10] combined regret theory with IIS prospect theory and proposed a new three-way decision method to further combine three-way decisions with behavioral decisions. [PERSON] et al. [11] proposed an opinion classification method combining three-way decisions with fuzzy concepts and semantic concepts to solve the problem of reducing the boundary area and maintaining high accuracy. In order to deal with the stability of the conflict system being affected by different preferences of decision makers, [PERSON] et al. [12] combined three-way decisions and conflict analysis with a grey system to establish a new conflict analysis model. In order to reduce the risk of decision-making errors and express linguistic uncertainty, [PERSON] et al. [13] combined double-layer hesitant fuzzy term sets with multi-attribute three-way decision making. Recently, researchers focused on making reasonable decisions with limited info to reduce decision risks. [PERSON] et al. [14] combined the fuzzy attribute concept with the three-way decision model and utility theory and proposed the three-way utility decision model. In multilevel data, obtaining acceptable decisions at various granularities is crucial. [PERSON] et al. [15] proposed a multi-granularity hierarchical sequential three-way decision model to advance three-way decisions. [PERSON] et al. [16] combined Sigmoid utility with three-way decisions using Pythagorean fuzzy sets to solve related problems. [PERSON] et al. [17] constructed three fuzzy hesitant three-way decision methods to calculate the contingent probability of the target in the fuzzy hesitant information decision system without class labels. [PERSON] et al. [18] combined three-way decisions with interval values to propose a new method for solving multi-attribute decision-making problems in uncertain environments. In order to reduce the influence of different attribute types on decision results, [PERSON] et al. [19] integrated TOPSIS and regret theory into three-way decisions to settle multi-attribute decision-making difficulties in fuzzy environments without changing attribute types. The integration of three-way decisions and granular computing offered a befitting idea and method for the thinking of cognitive science and the trialization of information processing. Sequential three-way decisions are a classic representation of three-way granular computing, which makes multi-stage decisions through a series of transaction-optimization (TAO) models. [PERSON] et al. [20] integrated three-way decisions and multiple granularities to enhance the domain system's hierarchy and structure.