大数据背景下物流服务订单分配

针对已存在的多级物流服务供应链订单分配中没有充分考虑客户的最佳配送时间和需求的问题,提出了在大数据背景下,利用大数据的知识分析客户的点击量、浏览时间和销量之间的关联性,预测客户的需求、分析客户的位置数据来预测客户的最佳配送时间.基于大数据的预测结果,以物流服务集成商最小化服务成本为目标,建立三级物流服务供应链的订单分配优化模型,并通过实例仿真进行了验证.结果表明,基于大数据预测的销量和配送时间更贴近客户实际需求,在保证客户服务质量的情况下,获得问题的最优解.

Order allocation of logistics service under background of big data

In order to solve the problem that the optimal delivery time and demand of customers in the existing order allocation of multi level logistics service supply chain are not fully considered, under the background of big data, a method to analyze the correlation between the clicks of customers, browsing time of customers and sales and to predict the demand of customers with the knowledge of big data was proposed. In addition, the best delivery time was predicted with the location data of customers. According to the predicting results under the background of big data, an optimization model for the order allocation of three level logistics service supply chain was established with the objective of minimizing the cost of logistics service integrator, and the model was verified with an example. The results show that the sales and delivery time predicted based on the big data are closer to the actual demand of customers, which can obtain the optimal solutions on the premise of ensuring the service quality for customers.