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发表时间：2014-01-01

发表刊物：管理科学

所属单位：经济管理学院

期号：6

页面范围：103-113

ISSN号：1672-0334

摘要：In the e-commerce on-line order picking system, customer orders′arrival time and goods cannot be informed in ad-vance.With the constraints of picking equipment capacity and pickers′number, the order batching optimization approach, which focuses on the batching time and batching strategy, is proposed to pick out maximum orders in the shortest service time before the due time.The on-line order batching mixed-integer programming model considering orders′due time is established to minimize the valid average service time of distributed orders.To solve this problem, the improved fixed time window order batching algo-rithm is proposed.The order is identified as the urgent one if its remained operation time is between lead time and distribution setup time.Based on orders′different urgent level, we propose the on-line order batching rules while taking into account urgent degree and similar degree.Through a series of experiments where the orders are generated from 14:00 to 18:00 based on Poisson distribution (λ=17), we compare the results with ones of traditional on-line order rules.Several enlightening findings are dis-covered:If considering orders′due time, the number of distributed orders is bigger, the batches′total service time and the dis-tributed batches′valid average service time are shorter, and the number of delayed orders is smaller and delayed time is shorter. Meanwhile, if considering orders′due time, with the increase of the number of order pickers, the delivery rate improves in differ-ent degree, and the increase of delivery rate is larger than the one of traditional rules.However, the increasing of delivery rate is a progressive decline.

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