Emergency rescue planning under probabilistic linguistic information: An integrated FTA-ANP method

Abstract

In the last few years, emergencies have brought about catastrophic casualties and property loss. After an emergency, the emergency manager who is in charge of the rescue work has to identify an optimal rescue plan from several alternatives. Therefore, it is necessary to develop an effective method for selecting an optimal rescue plan to reduce the damages of emergencies. Usually, an emergency decision has three features: time urgency, incomplete information and potential severe results. While it is difficult to provide the accurate numerical evaluations with the incomplete information under limited time, the probabilistic linguistic term set (PLTS) is introduced to represent the opinions of emergency decision making panel (EDMP) in this paper. In this way, EDMP can provide suggestions with linguistic terms, and the manager can directly collect qualitative opinions in a short time. In addition, fault tree analysis (FTA) is used to evaluate the probabilities of potential severe results, and analysis network process (ANP) is adopted to derive the weights of criteria that determining the damages of potential severe results. Then, we can quantify the potential severe results of alternatives so as to choose the one with the minimum damages. In this study, we first attempt to integrate PLTS and FTA-ANP method to comprehensively consider the three features of emergency decision to select an optimal rescue plan. Finally, a case study is employed to verify the feasibility of the proposed method, and the comparisons and discussion are presented to show the rationality and novelty of this study.