Robust optimization of multi-objective and multi-period emergency materials scheduling considering fairness and timeliness

The number of cases surged in the early stage of the outbreak of new pneumonia, and the demand for medical materials fluctuated greatly. How to meet the needs of hospitals and transport medical materials to the demand point in time under the uncertain and dynamic environment is an urgent problem to be solved. Firstly, this paper predicts the demand of emergency medical materials based on SEIR infectious disease dynamics model. Secondly, the entropy weight method is introduced to determine the urgency of demand points, ensure the priority of demand points with high urgency, on this basis, a multi-objective and multi-period robust optimization model is established by maximizing the weighted satisfaction rate and minimizing the vehicle routing problem. Finally, the emergency medical material scheduling in Wuhan is taken as an example. The results show that the optimization model can improve the fairness and timeliness of emergency materials distribution to a certain extent, and effectively alleviate the impact of demand dynamics and uncertainty on the scheduling scheme, it is of great significance to the dispatch of emergency materials under the epidemic situation.