Research On Optimal Scheduling Of Emergency Materials In Major Public Health Emergencies

In recent years,public health incidents have occurred frequently,resulting in varying degrees of casualties and economic losses.In 2019,the outbreak of COVID-19 has been greatly affected by the epidemic.In order to reduce the losses caused by the epidemic,we must establish a scientific and efficient dispatching plan for emergency materials,so as to ensure the distribution of emergency materials and the efficiency of distribution,meanwhile enhance the stability and timeliness of the entire emergency management network.This paper studies the allocation and transportation of emergency materials in the initial stage of public health emergencies,and proposes an emergency material scheduling model based on priority.Priority is determined by the demand urgency and time tolerance of the demand point,and the fairness index is constructed according to the priority and Gini coefficient.In the case of material shortage at the initial stage of emergency,we established a two-stage model to optimize the fairness and efficiency of emergency logistics.In the initial stage,the material allocation model is established with the goal of maximum fairness.On the basis of this distribution scheme,we established a dual objective optimization model with minimum scheduling time and minimum penalty cost.The multi-objective problem is transformed into a single objective problem by using the epsilon constraint method.The maximum minimum ant colony system and the ant colony system are combined through reinforcement learning mechanism to design a heterogeneous ant colony algorithm,which solve the single objective optimization problem.The algorithm introduces reinforcement learning mechanism to exchange and update the information of ant colony.The reward factor is set to adjust pheromone,increase the diversity of solutions and improve the convergence of the algorithm.Simulation experiments on Solomon dataset show that this model can effectively formulate the emergency material scheduling scheme,taking into account the requirements of fairness and efficiency.Compared with other heuristic algorithms,the algorithm designed in this paper has better convergence and diversity,and can jump out of the local optimum,and the quality of the solution is significantly improved.Finally,the experimental analysis is carried out under the specific case of COVID-19,which verifies the impact of the priority of the demand point on the scheduling scheme.The experimental results show that the model can help decision-makers to establish a scientific and reasonable emergency material scheduling scheme.