Multi-objective optimization approach to define risk layer for seismic mitigation

Earthquakes have caused more than 50,000 lives and $4,000 million economic losses over a period of 20 years in Iran. Having accurate risk assessment and effective future plans can significantly reduce these losses. In this paper, two key parameters, which are effective in both human and economic loss reduction, have been defined, one of which is the number of saved lives before and after taking mitigation measures and the other one is the household expense ratio related to the cost of earthquake mitigation measures. For this reason, Shiraz city, located in the southwest of Iran, has been selected for evaluation. Detailed building taxonomy is performed, and for seismic vulnerability evaluation, vulnerability curves exclusively derived for Iranian buildings are used. Multi-objective genetic algorithm optimization method is conducted to find a balance between the costs of seismic mitigation measures and number of casualties. This balance proposes the extent of mitigation actions which is representative of a specific layer of risk and is identified as a set of Pareto Front for all types of buildings. The optimal risk layer can play a vital role in shaping management policies for decision-makers in order to reduce the inherent risk of country.