第三方物流中货物需求量的灰色模型预测及应用

Forecasting Merchandise Demands with Grey Model and its Application in the 3^(rd) Part Logistics

针对第三方物流系统中的各种资源利用率不高而导致的高成本、低收益等问题,提出了通过对货物需求量进行预测来提前对各种资源作合理的安排,从而提高物流企业效率的想法。由于物流企业及其货物历史数据较少,而灰色理论预测对于原始数据需求量也较少,因此采用GM(1,1)模型来进行年和月需求量的预测。通过实例并与其它算法进行比较分析,验证了该算法在物流需求量预测中的可行性。文章最后给出了该算法在杭州富日物流公司的智能信息协作平台上的应用示例。

This paper aims to deal with the problems such as high costs,low benefits which are caused by low usage of all kinds of resources in the 3^rd part logistlcs.Thus an idea of forecasting merchandise demands has been put forward to arrange all kinds of resources ahead of schedule to improve the efficiency.With regard to the shortage of history data of logistics companies and their merchandises ,the GM（1, 1 ） is employed to forecast year and month merchandise demands for its less requirement on data.Its feasibility is validated by an example and a comparison with other forecasting algorithms.Finally the application of the algorithm is demonstrated in the intelligent information collaboration platform of Hangzhou Furl Logistics Co.Ltd.