Estimation of relief supplies demands through fuzzy inference system in earthquake condition

Natural disasters such as earthquakes have a destructive impact on urban infrastructures and their performance. Due to the existence of inherent uncertainty in natural disasters, related organizations are not able to optimally use the critical infrastructures to reduce destructive effects. Also, estimating the demand for relief commodities according to various scenarios has always been a concern for decision makers and relief organizations. The correct estimate of demand can reduce the time of relief operations and can greatly reduce human casualties. In this paper, the demand forecast for relief commodities will be as the output of the fuzzy inference system. The proposed mechanism has been tested in a case study of Tehran city. The results of this research can be useful for many decision making centers, including the fire department, the Red Cross, hospitals and so on. Estimation of demand for relief commodities using the fuzzy inference system for different scenarios and considering a case study for a possible earthquake in Tehran are the contributions of this research.