能力约束下多产品物流频繁路径挖掘算法仿真  

Multi-Product Logistics Frequent Path Mining Algorithm Simulation under Capacity Constraints

作　　者：张铁宝[1] 李桂娥[1] ZHANG Tie—bao;LI Gui—e(Business College,Shanxi University,Taiyuan Shanxi 030031,China)

机构地区：[1]山西大学商务学院

出　　处：《计算机仿真》2019年第12期249-252,262,共5页Computer Simulation

基　　金：山西省教育科学“十三五”规划课题(GH-18170)

摘　　要：针对当前多产品物流频繁路径挖掘算法运行时间慢,导致时间效率低的问题,提出一种新的多产品物流频繁路径挖掘算法。按照多产品物流频繁路径不同时间段的先后顺序,将物流频繁路径转为时间和位置序列,求出频繁序列;按照时间对多产品物流频繁路径进行聚类,并计算步进时间阈值,通过对频繁有向边的计算,以及对支持路径和支撑有向边的提取,最终实现了能力约束下多产品物流频繁路径的挖掘。实验结果表明,提出算法在对多产品物流频繁路径挖掘时,挖掘的频繁路径数量下降,运行速度加快,效率较高;在数据量巨大的情况下,所提算法的执行时间小于其它算法,并且随着数据量的增加,提出算法的优势更加明显。At present,the multi-product logistics frequent path mining algorithm runs slowly and leads to low time efficiency.Therefore,a new multi-product logistics frequent path mining algorithm was put forward.According to the sequence of multi-product logistics frequent paths at different time,the logistics frequent path was converted into the time series and position series to find frequent sequences,and then the frequent sequence was found.According to the time,the frequent paths of multi-product logistics were clustered and the step-time threshold was calculated.Through the calculation of frequent directed edges and the extraction of support paths and support directed edges,the frequent paths in multi-product logistics under capacity constraints were finally mined.Simulation results verify that the proposed algorithm reduces the number of frequent paths and accelerates the running speed in mining frequent path of multiproduct logistics,so it has high efficiency.In the case of massive data,the execution time of the proposed algorithm is less than other algorithms.With the increase of data,the proposed algorithm becomes more important.

关 键 词：能力约束下 多产品 物流频繁路径 挖掘 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]