چكيده به لاتين
Despite of great prosperity in different scientific area, earthquake prediction is partially inaccessible, so getting prepared against this natural disaster is vital. On the on hand, statistical data related to human and finantial losses shows disaster management is not perfect to save the susceptible world, hence, practical researches in humanitarian logistics to minimizing these losses, are essential. This is evident that practical researches in disaster management in emergency situation help Decision Makers to design efficient networks and find affordable and convenient policies.
In emergency situation after earthquake occurrence, local and international suppliers offer assistance to the affected country. These suppliers try to minimize their total cost and the affected country seeks to minimize unsatisfied demands and total cost. To modelize this situation a multi-level programming based on uncertainty has been used. In the upper level, Hilal Ahmar acts as the leader which tries to locate its relief bases in the first stage, and make distribution and evacuation decisions in the second stage. In the lower levels foreign countries and local supplier try to minimize their cost. Finally, we used Mont-Carlo simulation and p-robust optimization to capture political constraints after earthquake occureance.
Keywords:
Relief Chain Management, Two-stage stochastic programming, Multi-level programming, Stochastic Programming, Mont-Carlo simulation.
