Research On Urban Flood Emergency Supplies Dispatch And Transportation Optimization

Flood disasters are a common natural disaster that seriously harms society,economy and people's lives and property.The outbreak of urban flood disasters often generates a large number of urgent relief supplies,and it is necessary to quickly,efficiently,and accurately send a variety of emergency supplies to the disaster area.This thesis addresses the needs of emergency logistics practices in the event of urban floods,and comprehensively applies theoretical methods such as logistics management,systems engineering,intelligent optimization,and decision support to research and solve emergency resource demand forecasting and emergency material dispatch and distribution in urban flood disaster emergency logistics.Some key common issues such as the optimization of transportation resource allocation.In order to reliably provide necessary relief supplies,with the goal of maximizing time efficiency and minimizing disaster losses,and taking into account the cost loss resulting from material storage,deployment,and transportation,a theory for the optimization of urban flood control and distribution systems is established.The research work carried out in this paper mainly includes:The sudden and uncertainties of the flood disaster make it difficult to collect large sample data to forecast the demand of emergency materials quickly and accurately.Based on this,this paper proposes an improved GM(1,1)dynamic forecasting model based on the gray system theory,and constructs the dynamic demand model of emergency materials in combination with the inventory management method,and takes the flood disaster in March 2016 as the real case,The validity of the model proposed in this paper is verified.The results show that the improved GM(1,1)model is feasible and practicable,and it has higher prediction accuracy than the traditional GM(1,1)model.Scheduling on emergency relief supplies is the important security in the natural disasters and emergency rescue work.Transportation and distribution of emergency supplies scientifically is the key to implement efficient relief.A two-stage model of emergency relief supplies with obverse transportation and distribution and reverse logistics is established based on the analysis of flood disaster features in the emergency supplies logistics,where helicopter,vehicle and train,three types of the transportation are considered.The objective is to minimize the total cost of the transportation and maximize the time satisfaction of the disaster area.The particle swarm optimization algorithms are derived for the obverse and reverse logistics decision of the transportation and distribution of the emergency relief supplies in this paper.The computational results prove the effectiveness and stability of the model and algorithm.In order to solve the problem of emergency material allocation in flood disaster area,this paper constructs the research framework combined with "Internet +",and designs the hybrid optimization method which realizes the interaction between decision layer and executive layer.Based on the structure,the emergency rescue distribution center uses the initial data obtained from the implementation participants.Firstly,real-time demand point estimation is provided for the material needs of the disaster area.Secondly,unsupervised clustering analyzes on the correlation properties of flood disaster area to obtain the division of the region based on the rescue frequency,the casualty rate,the rate of the vulnerable groups,the rainfall and the degree of damage to the building.Subsequently,the urgency priority of the material distribution area should be determined.And then,according to the weight,the remaining relief supplies of emergency inventory are allocated to the disaster areas,which disaster area material demand estimates is updated immediately,until the demand in the disaster area reached the preset level of satisfaction.In the end,the results show that the hybrid optimization method can fully optimize the system in terms of demand satisfaction ratio and time allocation cost,and make effective use of the golden rescue period to complete the humanitarian rescue.For emergency scheduling and distribution after disaster,the three-level multi-source distribution system is treated as research object.This thesis constructs a mathematical model about maximum satisfaction level based on equity.In the model,the effect of updating real-time traffic information on distribution scheme is also take account.Also,a hybrid genetic algorithm with tabu search algorithm is improved.The results show that the real-time traffic information has a higher degree of disaster satisfaction and faster response than static scenarios.The research results of this thesis can provide reference for China's urban flood disaster emergency rescue to improve the efficiency of it,enhance satisfaction for disaster relief,reduce economic costs,reduce disaster losses,and enhance China's urban emergency rescue capabilities.