Under the threat of bio-terrorism,this paper aims at improving the emergency rescue system's ability of dealing with a public health emergency.Focusing on the demand network,this research establishes the emergency...Under the threat of bio-terrorism,this paper aims at improving the emergency rescue system's ability of dealing with a public health emergency.Focusing on the demand network,this research establishes the emergency rescue supply storage network under a danger diffusion environment.Combined with the infectious disease diffusion model,the traditional set covering model is rebuilt taking the decision optimization of reserve quantity into consideration.Under the premise of a certain emergency service level,the collaborative location optimizing model of an emergency rescue supply storage network is established in order to minimize the sum of the building costs and the preserving costs.The model is proved to be effective through numerical simulation.The collaborative location optimization of the nodes of the emergency rescue supply storage network and the reserve quantity of each storage node is realized.展开更多
基金The National Natural Science Foundation of China(No.70671021)the National Key Technology R&D Program of China during the11th Five-Year Plan Period(No.2006BAH02A06)
文摘Under the threat of bio-terrorism,this paper aims at improving the emergency rescue system's ability of dealing with a public health emergency.Focusing on the demand network,this research establishes the emergency rescue supply storage network under a danger diffusion environment.Combined with the infectious disease diffusion model,the traditional set covering model is rebuilt taking the decision optimization of reserve quantity into consideration.Under the premise of a certain emergency service level,the collaborative location optimizing model of an emergency rescue supply storage network is established in order to minimize the sum of the building costs and the preserving costs.The model is proved to be effective through numerical simulation.The collaborative location optimization of the nodes of the emergency rescue supply storage network and the reserve quantity of each storage node is realized.
