A Knowledge-Based Multi-Criteria Decision Support System Encompassing Cascading Effects For Disaster Management

This paper describes a knowledge-based decision support system (KB-DSS) to improve the preparedness of crisis situations induced by natural and technological hazards. The proposed KB-DSS aims to manage the potential cascading effects generated by a triggering hazard assessing the possible event time histories based on interconnected probabilistic simulation models. From a methodological point of view, a decision model based on two Multi-Criteria Decision-Making (MCDM) algorithms follows a cascading effect simulation model. This combination allows to support the decision maker in comparing a set of mitigation strategies on the basis of their expected impacts and his priorities. The algorithm is based on an ensemble approach, which combines decisions over an array of possible impact scenarios, instead of only relying on the average impact scenario. An application of the KB-DSS to the case of a possible reactivation of Nea Kameni volcano in Santorini is presented to show how the proposed architecture could be applied to a real case. The proposed methodology supports the emergency planners in making the best decisions supporting them also in the choice of the best timing for the intervention.