Designing Humanitarian Relief Supply Chains by Considering the Reliability of Route, Repair Groups and Monitoring Route

Most humanitarian relief items investigations try to satisfy demands in disaster areas in an appropriate time and reduce the rate of causality. Time is an essential element in humanitarian relief items; the quietest response time, the more rescued people. Reducing response time with high reliability is the main objective of this research. In our investigation, monitoring the route’s situation after occurrence disaster with drones and motorcycles is planned for collecting information about routes and demand points in the first stage. The collected information is analyzed by the disaster management to determine the probability of each scenario. By evaluating collected data, the route repair groups are sent to increase the route’s reliability. In the final step, the relief items operation allocates the relief items to demand points. All in all, this research tries to present a practical model and real situation to survive more people after the occurrence of the disaster. An exact solver solves the evolutionary model in small and medium scales; the developed model in big scale is solved by Grasshopper Optimization Algorithm (GOA), and then results are evaluated. The evaluation results indicate the positive effect of valid initial information on the humanitarian supply chain’s performance.