Research on location-inventory-routing optimization of emergency logistics based on multiple reliability under uncertainty

Earthquakes, floods and other types of natural disasters are frequent and bring many devastating effects. The research related to emergency logistics has received much attention in recent years. In order to further improve the rescue efficiency and reduce disaster losses, a multi-objective two-stage stochastic programming model of location-inventory-routing of emergency logistics based on multiple reliability under uncertainty is addressed. The proposed model includes three types of uncertainty as demand, supply and transportation time, and two kinds of reliability as distribution center facilities and road access. It is used for integrated decision making in disaster preparedness and response stages. Factors such as material bulk procurement discount, pre-disaster budget, multiple transportation modes, capacity constraints, and disaster scenarios are considered comprehensively. Then, an algorithm was developed. A non-dominated ranking genetic algorithm (NSGA-II) is used to solve the developed model according to its characteristics. The validity of the model and algorithm is verified by conducting a case study on an earthquake in Sichuan, China, and the Pareto optimal solution set is obtained. Finally, sensitivity analysis of the parameters is performed to investigate the effect of changes in key parameters on the model solutions. Thus, some relevant management insights are provided. The results show that an appropriate increase in the pre-disaster budget can substantially reduce the response cost in the post-disaster period. In addition, increasing the number of resident helicopters within the material inventory by a certain amount can help reduce the total distribution time.