Operating mechanism of logistics concentrating goods based on stochastic service process
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摘要: 为提高物流网络节点(物流中心)的集货运作管理效率, 应用随机服务系统理论与方法描述了物流网络节点的集货过程及其特征, 与分散运作管理模式进行了对比, 研究了物流网络节点集货的运作机理, 建立了集货运作机理模型(马尔可夫排队模型)。算例分析结果表明: 在同等条件下, 与分散运作模式相比, 集货运作模式系统各项运行指标具有明显的优势, 服务设施利用率提高了23.4%, 货物在系统中的平均滞留时间缩短了56.12%;当繁忙程度为90%时, 分散运作模式系统运行指标发生急剧变化, 而集货运作模式的各项运行指标变化不明显, 货物在系统中的平均滞留时间不到分散运作模式下的1/5。Abstract: In order to raise the concentrating goods operating management efficiency of logistics network joints(logistics centers), the process and characteristic of concentrating goods were described by applying stochastic service system theory and method, concentrating goods operating mode(CGOM) was compared with decentralized operating mode(DOM), the operating mechanism of concentrating goods was studied, and CGOM's model(Markov queuing model) was constructed.The analysis result of a example indicates that the system running indices of CGOM are obviously superior to that of DOM, its service facilities' utilization ratio increases by 23.4%, system goods average staying time decreases by 56.12%;especially, its system running indices' change of DOM is rapid when system busy degree is 90%, but that of CGOM is not obvious, and the goods average staying time in CGOM system is less than 1/5 of that in DOM system.
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表 1 系统运行指标
Table 1. System running indices
指标 模式 集货运作模式(M/M/3)型 分散运作模式(M/M/1)型 服务设施(窗口)利用率(1-P0)/% 92.52 75.00(每个服务点) 客户(货物)必须等待的概率/% 56.75 75.00 平均排队等待服务的货物批数Lq 1.70 2.25(每个服务点) 系统中平均滞留的货物批数Ls 3.95 9.00(整个区域) 货物在系统中平均滞留时间Ws/min 26.33 60.00 货物在系统中平均等待时间Wq/min 11.33 45.00 
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