基于联合介数中心度的铁路货运嵌入社会大物流系统网络结构优化

Network Structure Optimization of Railway Freight Embedded in Social Logistics System Based on Combination Betweenness Centrality

社会大物流系统是一个无标度网络,存在明显的集群现象。铁路货运系统作为另一个群体嵌入社会大物流系统,需要在优化网络结构的同时,考虑群体之间的连接和群体内部的连接。基于Barabási-Albert算法的无标度网络生成机制,通过理论推导和实验仿真,分析联合介数中心度及其标准差与网络货流量的关系。研究认为,铁路货运系统节点嵌入社会大物流系统时,应当选择联合介数中心度较大而其标准差较小的节点进行嵌入,通过增加捷径路径可改善中枢节点的连接性,以及减轻和均衡中枢节点的负荷,使得整个物流系统更高效地运作和降低网络优化的成本。

Social logistics system is a scale-free network with obvious group phenomenon. When we study the network structure optimization of railway freight embedded in logistics system, we should not only consider the connection between groups but also the connection within groups. Based on the scale-free net- work generating mechanism of Barabasi-Albert （BA） algorithm, we analyze the relationship between joint betweenness centrality together with its standard deviation and network freight flow volume through theo- retical deviation and experiment simulation. We draw the conclusion that the junction of railway freight node with other nodes in logistics system should be chosen in the node with higher joint betweenness centrality and lower standard deviation, and the connection of hub node can be improved by increasing shortcut paths. The new optimization algorithm can alleviate and balance the load of hub node, and make the operation of the whole logistics system more efficiently as well as lower the cost for network optimization.