最小化拆单率的在线零售商多仓商品摆放优化策略研究

发布时间：2018-04-13 04:32

本文选题：在线零售 + 运营管理　；参考：《管理工程学报》2017年03期

【摘要】：拆单是指一张订单需要从多个仓库独立进行配送,或由一个仓库在不同时间分别配送,而这会额外增加商家的物流成本。本文对在线零售商多个仓库的商品摆放策略进行了研究,目的是降低由于商品摆放策略不同所引起的拆单。文中考虑了总体不缺货情况下,基于品类和数量的两类拆单情况,并建立数学模型,改进了热销品算法(Bestseller)得到了环形算法(Loop),对相应仿真问题进行求解,并与原热销品算法进行对比。结果表明环形算法能够在兼顾各配送中心负载的同时进一步降低品类拆单率,进而降低总体拆单率。备货量的分析表明,在线零售商可以通过增加备货量来降低甚至消除数量拆单的影响。对品类约束的研究表明,在单仓商品品类较少时,品类拆单对总的拆单率影响更大;单仓商品品类较多时,数量拆单影响更大。效率方面,由于环形算法不需要计算相关性矩阵,效率相比热销品算法要高。
[Abstract]:A single order is an order that needs to be delivered independently from multiple warehouses or distributed separately by one warehouse at different times, which adds to the merchant's logistics costs.In this paper, we study the commodity placement strategies in multiple warehouses of online retailers, in order to reduce the demolitions caused by different commodity placement strategies.In this paper, under the condition of no shortage of goods in the whole system, two kinds of unpacking cases based on category and quantity are considered, and the mathematical model is established, and the hot selling algorithm (Bestseller) is improved to get Looper algorithm, and the corresponding simulation problem is solved.And compared with the original hot selling algorithm.The results show that the ring algorithm can further reduce the rate of single removal and then reduce the total rate of single removal while taking into account the load of each distribution center.The analysis of stock volume shows that online retailers can reduce or even eliminate the impact of quantity withdrawal by increasing stock volume.The research on category constraints shows that when the single warehouse commodity category is less, the category dismantling single has more influence on the total single removal rate, and the quantity of the single warehouse commodity category has more influence on the total single removal rate.In terms of efficiency, because the ring algorithm does not need to calculate the correlation matrix, the efficiency of the algorithm is higher than that of the hot goods algorithm.
【作者单位】：华中科技大学管理学院;
【基金】：国家自然科学基金资助项目(71171088、71131004) 中央高校基本科研业务专项基金资助项目(2014YQ002) 湖北省科技计划软科学类项目(2014BDF112) 教育部新世纪优秀人才基金资助项目(NCET-13-0228)
【分类号】：F274;F724.6

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