Affiliation:
1. School of Management, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
Abstract
When a public health event occurs, it is very difficult to guarantee a stable supply of emergency medical supplies; this has a great impact on the efficiency of emergency rescue work. Therefore, this paper takes the problem of transporting and stockpiling emergency medical supplies in modern public health events as its research theme. We use the SEIRD (susceptible, exposed, infected, recovered, and dead) system dynamics model to predict the number of infected people and the demand for emergency medical supplies and obtain a number of single-day demand of 0.3 N + 0.15 I − 0.15 R − 0.3 D. An index system based on 11 indicators was established and the demand urgency function was designed. A bi-objective vehicle routing problem with time windows (VRPWT) for emergency medical supplies considering demand urgency and response cost minimization is established and solved using particle swarm optimization (PSO). To test our approach, the model is simulated using the initial COVID-19 data of six cities in China. Finally, we obtain the prediction of these six demand points and the demand urgency, and the PSO algorithm can reach the optimal solution in this VRPTW problem. The optimal travelling distance is about 1461.45 km and the total cost is 6726.5 Yuan. This simulation confirms the model’s rational and feasibility and presents suggestions to cope with modern public health events.
Funder
National Natural Science Foundation of China
Jiangsu Social Science Foundation
Suzhou Science and Technology Bureau
Nanjing University of Posts and Telecommunications
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
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