Saeed Elahi’s scientific contributions

Natural disasters, including floods, earthquakes, storms, droughts, affect the lives of many people in different regions of the world and Due to their unpredictability, inflict heavy and irreversible damages to nations. These natural disasters mostly cause many fatal and financial damages. The large extent of the damages and fatalities of these disasters in different cities of the worlds has recently attracted for relief missions to damaged regions and reducing the impacts of these disasters. Therefore, relief chains are responsible for supplying basic needs and aiding the injured people at appropriate locations in the fastest time. Support and relief logistics play a determinant role as one of the main pillars of disaster management. In case of any disruption in this role, the whole disaster management process is disturbed. Relief logistics includes all processes for estimating, preparing, planning, predicting, and preventing, supply, transportation, maintenance and distribution of commodities, and rescue teams. According to the existing research, there has been no research to propose a model in relief logistics using stochastic robust optimization with goals of increasing the satisfaction of the injured, which are transferred to medical centers, and increasing the satisfaction of affected areas by maximizing commodity coverage, as well as minimizing costs, pre-location for inventory management and organizing transportation vehicles to transfer commodities. Therefore In this paper, a bi–objective model, multi–product and multi–vehicle, under uncertainty environment is proposed. The first objective is maximization of commodity covering transferring to affected areas and the second one is Minimization of total cost. Due to unpredictable of natural disasters and indistinctive level of disaster, some of dependent parameters such as demand of relief commodity are considered uncertain. To solve the proposed bi-objective model under uncertainty, a stochastic robust optimization method and to solve bi-objective model a fuzzy goal programming approach have been adopted. Besides, a case study and necessary sensitivity analysis has been evaluated to prove the efficiency and applicability of the model.