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考虑逆向物流的应急物资配置流程SPN建模分析 被引量:7

Stochastic Petri Net modeling analysis of emergency resources allocation process considering reverse logistics
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摘要 应急物资的高效快速配置是降低灾害损失和顺利实施应急救援的有力保障。应急逆向物流包括废旧物资的回收利用以及可重复利用物资的回收再利用,能起到缓解应急物资匮乏,减少环境污染的作用。本文根据随机Petri网理论,构建考虑逆向物流的应急物资配置模型,通过对同构于该模型的马尔可夫链进行仿真,求得各种状态的稳态概率,结合马尔可夫链性质对关键因素进行静态分析和动态分析;通过"雅安地震"的案例应用表明,当地震灾害发生时,此模型可以反映各因素对应急物资配置整体流程的影响,并通过数值变化趋势反映不同条件下应急物资配置的关键环节,可以为灾后救援和应急物资的利用提供理论支持。 Efficient and rapid allocation of emergency resources is a powerful guarantee for reducing disaster losses and smoothly implementing emergency rescue. Emergency reverse logistics,including the recycling of waste resources and the recycling of reusable resources can alleviate the shortage of emergency supplies and reduce environmental pollution. Using Stochastic Petri Net( SPN),we first establish an emergency resources allocation model considering reverse logistics,and then the steady state probabilities of various states are obtained by Markov chain simulations. Moreover,static and dynamic analyses are conducted on key factors of this model based on Markov chain properties. Finally,Ya’an earthquake is used as a case study. The simulation results show that our model is able to reflect the impacts of various factors on the entire emergency resources allocation process after earthquake disaster occurs. And the key processes of emergency resources allocation under different conditions are identified by numerical analyses,which can provide theoretical supports for rescue process of posdtdisaster relief as well as utilization of emergency resources.
作者 余佳 王维莉 韩新 范勤勤 胡志华 YU Jia;WANG Weili;HAN Xin;FAN Qinqin;HU Zhihua(Logistics Research Center, Shanghai Maritime University, Shanghai 201306, China;Shanghai Institute of Disaster Prevention and Relief, Shanghai 200092, China)
出处 《中国安全生产科学技术》 CAS CSCD 北大核心 2019年第4期12-18,共7页 Journal of Safety Science and Technology
基金 国家重点研发计划项目(2016YFC0800200) 国家社会科学基金项目(18BGL103) 上海市社会科学基金项目(2017BGL015)
关键词 应急物资 逆向物流 随机PETRI网 马尔可夫链 性能分析 emergency resources reverse logistics Stochastic Petri Net Markov chain performance analysis uncertainty
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