A knowledge-based multi-criteria decision support system encompassing cascading effects for disaster management

Purpose This paper describes a knowledge-based Decision Support System to improve the preparedness, the response capacities and the management of crisis situations induced by natural and technological hazards. The proposed DSS aims at managing the potential cascading effects generated by a triggering hazard, assessing the possible event time histories based on interconnected probabilistic simulation models. Methodology/Approach A decision model based on two Multi-Criteria Decision Making 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 her/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. Findings An application of the DSS to the case of a possible reactivation of Nea Kameni volcano in Santorini is presented in order to show how the proposed architecture could be applied to a real case. The case study shows how the end user could benefit from the DSS functionalities, accounting for the expected impacts of selected mitigation strategies in a sustainable vision. Originality/Value 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. Moreover, the possibility of assigning weights to economic and environmental-related variables in Multi-Criteria Decision Making algorithms allows the decision maker to favour sustainable choices, both in economic and environmental terms.