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大规模突发事件应急血液采集动态模型 被引量:13

Dynamic model for emergency blood collection in large-scale sudden-onset emergencies
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摘要 为了保障大规模突发事件的应急血液供应,同时降低应急血液报废量,针对应急血液库存控制的特性,提出了一种应急血液采集动态模型,并给出了应急血液库存状态转移方程,以及血液过期报废量、血液需求短缺量、采血能力约束的表达式.通过数值算例验证了上述模型的有效性,并进行了模型参数的灵敏度分析.研究结果表明,该模型可以很好地解决应急血液报废问题;安全库存水平、目标存量水平、预测误差、需求波动对应急血液采集和库存控制效果均有重要影响,应适度提高目标存量水平和安全库存,适度高估应急血液需求,并确定合理的应急血液库存控制参数. To ensure the supply and avoid the waste of emergency blood after a large-scale sudden-onset emer- gency, this paper develops a dynamic model for emergency blood collection according to the characteristics of emergency blood inventory control. This paper also derives the state transfer equations for emergency blood inventory, and formulates the expressions for blood outdating, blood shortage and blood collection capacity. A numerical example is presented to illustrate the validity of the model, as is accompanied by a sensitive analysis of model parameters. The results show that the proposed model is helpful in reducing the waste of emergency blood. The safety stock level, target stock level, prediction error, and demand fluctuation all have a significant impact on emergency blood collection and inventory control decision. It is necessary to moderately increase the safety stock and target stock level, overrate the emergency blood demand, and determine reasonable parameters for emergency blood inventory control.
作者 马祖军 周愉峰 Ma Zujun Zhou Yufeng(Institute for Logistics and Emergency Management, School of Economics and Management, Southwest Jiaotong University, Chengdu 610031, China School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China Chongqing Engineering Technology Research Center for Information Management in Development, Chongqing Technology and Business University, Chongqing 400067, China)
出处 《系统工程学报》 CSCD 北大核心 2017年第1期125-135,共11页 Journal of Systems Engineering
基金 国家自然科学基金重大研究计划培育项目(90924012) 国家自然科学基金资助项目(71672154) 教育部人文社会科学研究规划基金资助项目(16YJA630038)
关键词 突发事件 血液采集 动态模型 库存控制 sudden-onset emergency blood collection dynamic model demand forecasting
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