大数据条件下网络零售商的经济批量问题

为了研究一个有限计划期内,在供应商处于大数据的条件下,网络零售商满足客户个性化需求的补货及发货批量策略制定问题,对大数据进行预处理,筛选有效的客户浏览行为,通过信息过滤,优选服务供应商.由于建立的批量问题模型具有一定的复杂性,设计多项式算法求解批量模型,从而获得问题的最优解,选择最终供应商及制定批量策略.结果表明,该处理方法具有一定的有效性,为大数据条件下网络零售商满足客户个性化、定制化需求的经济批量问题提供了解决方法.

Economic lot-sizing problem of online retailer under condition of big data

In order to study the establishment problem of replenishment and delivery lot-sizing strategy for online retailers in satisfying the personalized customer demands within a finite planning period when the suppliers are under the condition of big data, the big data were preprocessed, the effective customer browsing behavior was screened, and the service suppliers were optimized and selected through information filtering. Due to the complexity of the established lot-sizing problem model, a polynomial algorithm was designed to solve the lot-sizing model, and the optimal solution of the problem was obtained. In addition, the final supplier was selected, and the lot-sizing strategy was established. The results show that the proposed method has certain effectiveness, and can provide the solution for the economic lot-sizing problem of online retailer in satisfying the personalized and customized demands of customers under the condition of big data.