Expected consistency-based emergency decision making with incomplete probabilistic linguistic preference relations

In emergency decision making, it can be difficult for decision-makers (DMs) to identify all possible scenarios due to a lack of information and the evolution of emergency situations. Therefore, this paper presents an incomplete probabilistic linguistic term set (InPLTS), which is a generalized hesitant fuzzy linguistic term set (HFLTS). The InPLTS can more appropriately describe a case in which a DM considers several possible linguistic terms with uncertain probabilities. Furthermore, this work extends the InPLTS to an incomplete probabilistic linguistic preference relation (InPLPR) and proposes a complete algorithm based on an emergency fault tree analysis (EFTA) to estimate missing entries of the InPLPR. The work also investigates the expected consistency, acceptable expected consistency, and consistency-improving methods for the reasonable application of the InPLPR. Then, a consistency-based emergency decision-making method using the InPLPR is proposed to address issues related to a lack of information, uncertainties and dynamic trends. In using this method, DMs can evaluate emergency alternatives of different possible scenarios with the InPLPR, and the impacts of different emergency responses on the evolution of emergencies can also be considered. Finally, the InPLPRs and the abovementioned method are applied to a public health emergency decision-making process to illustrate the advantages of the proposed method. (C) 2019 Elsevier B.V. All rights reserved.