In addition, the platform provides the seismic risk impact in terms of direct economic losses, unusable or collapsed buildings and dwellings in the short and long periods and the expected number of homeless, victims and injured people. Such representation of an earthquake's consequences is a very useful support to the definition of seismic risk mitigation policies, helping in the identification of major risk areas requiring higher investments and facilitating the calibration of insurance premiums [7]. Today there are numerous technological strategies that can be adopted in order to achieve satisfactory seismic retrofit levels, thus reducing seismic risk. Although, as pointed out by the Organization for Economic Co-operation and Development [10], the effective financial management of earthquake risk requires governments to consider the best use of their limited resources. As a matter of fact, when the objective is the seismic risk mitigation of a large region where a wide number of buildings may need to be retrofitted, the challenge becomes more financial than technological. The limited amount of available resources generates the crucial issue of establishing how to spend the budget to achieve the highest regional seismic risk reduction, knowing that some buildings may not be covered by the retrofit's expense. This leads to a classical optimization problem aimed at finding the optimal trade-off between risk and the resources spent on the risk management program. The optimal decision would be the one minimizing the expected cost while maximum benefit could be yielded. Many recent studies investigate the use of multi-criteria decision methods (MCDM) within the context of regional seismic risk assessment. [PERSON] et al. [11] applied MCDM within a GIS environment to generate earthquake hazard maps using five main evaluation criteria (field topography, source-to-site distance, soil classification, liquefaction potential and fault/focal mechanism). The authors present the potentiality of integrating such maps with population and building data for the territory in order to provide regional risk information in terms of the potential impacts of earthquake effects. In a different way, [PERSON] and [PERSON] [12] combined MCDM and performance-based earthquake engineering (PBEE) in order to provide a viable tool for risk-informed earthquake early warning (EEW). In this case, the evaluation criteria assumed in the MCDM are the casualties, downtime and direct costs, i.e., the results of the PBEE, and are used to compare possible mitigation actions implementable when an EEW system triggers an alarm, finally determining the optimal one. [PERSON] et al. [13] implemented a multi-objective optimization approach based on a genetic algorithm in order to define the optimal mitigation measure for a given return period event according to two issues, i.e., (1) the household annual expenses, such as mandatory earthquake insurance premiums and mitigation costs; and (2) the effects of mitigation measures on saving human lives. A different procedure was introduced by [PERSON] et al. [14], consisting of the use of MCDM to create prioritization strategies to reduce the territorial seismic risk associated with public and strategic buildings. In particular, the proposed methodology compares the convenience of giving priority to the most vulnerable buildings, most exposed buildings (in terms of number of occupants) or to buildings located in the most severe seismic hazard zones. Other authors [15] focused on the assessment of the earthquake risk in historical urban fabrics with commercial value, based on the definition of the \"historic-commercial urban fabrics risk index\" (HCRI). This index can be estimated locally according to the contribution of hazard, vulnerability and response capacity, which are expressed by means of indicators and sub-indicators weighted through questionnaire surveys or expert judgement.