A new emergency decision support methodology based on multi-source knowledge in 2-tuple linguistic model

Knowledge is the foundation of emergency decision-making (EDM), in which the experts from multi-fields express their knowledge with multi-granularity linguistic model to assistant decision-making. Thus, the paper proposed a new decision support methodology to generate decision-making knowledge. In this paper, the framework of decision knowledge generation in the EDM was introduced firstly. To generate decision-making knowledge accurately and objectively, two objective models, which can effectively determine the weights of criteria and experts respectively, were built based on the tacit knowledge hidden in the original information. Then, the personal knowledge, generated by combining the normalized decision knowledge and the weight vector of criteria, is further aggregated into the collective knowledge by means of aggregation operator. Finally, an illustrative example is presented to verify the application of the proposed methods, and relevant discussions prove the results obtained from the proposed decision support methodology can improve the scientificity and accuracy of the EDM.