Optimization of a two-stage emergency logistics system considering public psychological risk perception under...

To enhance the level of emergency supplies deployment during earthquake disaster, this study focuses on emergency logistics in China. An integrated two-stage optimization framework is adopted to incorporate demand and time satisfaction indicators into the supply allocation and route optimization models, respectively. Firstly, historical data and seismic monitoring information are used to estimate the number of people affected and to forecast the need for emergency supplies; Secondly, the concept of psychological risk perception and the degree of urgency of requirements are introduced. Based on the modified prospect theory framework, this article replaces the sufficiency and shortage of demand with gains and losses to optimize the resource allocation policy. Thirdly, Particle Swarm Optimization (PSO) is used to improve the Sparrow Search Algorithm (SSA) for further model solving. The results of the study show that the two-stage optimization framework can significantly improve the rescue efficiency and rationality of resource allocation, and achieve the goal of prioritising the distribution of emergency supplies to regions with high urgency; In addition, the results of the sensitivity analysis indicate that it is crucial to determine the optimal proportion of the total amount of supplies, and the validation shows that the overall operational efficiency of PSO- SSA is higher, which provides a more reliable approach to dealing with similar emergency problems.