基于Matlab的模糊聚类法在零部件供应物流中的应用  

Application of Fuzzy Clustering in Spare Parts Supply Logistics Based on Matlab

作　　者：陈金升[1,2,3] 廖燕[1,2,3] 

机构地区：[1]武汉理工大学汽车学院,湖北武汉430070 [2]现代汽车零部件技术湖北省重点实验室武汉理工大学,湖北武汉430070 [3]汽车零部件技术湖北省协同创新中心,湖北武汉430070

出　　处：《物流技术》2017年第8期71-74,82,共5页Logistics Technology

摘　　要：由于零部件在汽车生产过程中种类繁多,在零部件供应物流中,依据零部件所占空间的大小,对零部件进行合理的搭配,可以充分利用物流运输车辆的有效空间,降低其运输成本。通过对零部件消耗体积的模拟,基于Matlab软件,采用模糊聚类法对汽车零部件搭配进行研究,分析了零部件装载运输过程中依据消耗体积进行聚类搭配模式,最终实现零部件物流配送的优化。In this paper, based on a simulation of the space consumption of automobile spare parts and using the Matlab program, we carried out a study of the mixing of the automobile spare parts in transit using the fuzzy clustering algorithm, and analyzed the mixing pattern of the spare parts during the loading and transportation processes based on their space consumption which ultimately led to the logistics and distribution optimization of the spare parts.

关 键 词：零部件 搭配 MATLAB 模糊聚类 供应物流 

分 类 号：F224[经济管理—国民经济] F252.2