A sequential three-way decision model based on linguistic Z-numbers - Yi Mao; Yaning Xu; Yuezhong Fan (PLoS ONE, 2025)
Linguistic Z-numbers (LZs), which uses both fuzzy constraint and reliability measure to describe information and has been widely used in various industries. However, as the amount of information needed to process increases, the relevant sorting methods are inefficient. Three-way decision model with decision-theoretical rough sets divides objects into three disjoint regions, namely acceptance,deferment, and rejection. In the subsequent process, only the objects that need delayed judgment are subdivided, which greatly reduces the amount of computation. Therefore, in order to improve the efficiency of decision making under LZs environment, we propose a sequential three-way decision model. Firstly, by considering both the fuzzy constraint and reliability measure, the three-way decision model with LZs (TWDZ) is proposed. Next, the concept of attribute hierarchy is proposed to prioritize attributes based on contributions to distinguishing alternatives. After that, combined with attribute priority, the objects in delay domain are constantly subdivided, and a sequential three-way decision model is proposed. Finally, considering the application background of double carbon economy, a practical case about selecting an optimal design of electric vehicles charging station is offered, and a comparative analysis was conducted to demonstrate the proposed STWDZ model.