CAJ | 학술논문

在电子商务在线订单拣选系统中,订单到达时间和订购商品等信息未知。针对拣选设备容量、员工人数等资源有限约束情况,研究在何时、对多少订单进行分批优化,以保证在订单完成期限前以最短的时间拣出最多的订单。构建考虑订单完成期限的在线订单分批混合整数规划模型,以最小化平均有效订单服务时间,采用改进的固定时间窗订单分批启发式规则求解模型,定义剩余操作时间在[前置时间,配送准备时间]内的订单为紧急订单,构建综合考虑紧急程度和相似度因素的在线订单分批算法。采用某配送中心14：00~18：00时间段内以泊松分布（λ=17）随机生成的订单进行数据实验,将实验结果与传统固定时间窗在线订单分批算法进行比较。研究结果表明,考虑完成期限时,系统拣选配送的订单数量更多,总服务时间和平均有效订单服务时间更短,且出现延迟订单的数量更少,延迟时间更短。拣选员工人数的增多在不同程度上提高配送率,且考虑完成期限时,配送率提高幅度要大于传统算法;但随着人数的增加,配送率的提高幅度呈降低趋势。
재전자상무재선정단간선계통중,정단도체시간화정구상품등신식미지。침대간선설비용량、원공인수등자원유한약속정황,연구재하시、대다소정단진행분비우화,이보증재정단완성기한전이최단적시간간출최다적정단。구건고필정단완성기한적재선정단분비혼합정수규화모형,이최소화평균유효정단복무시간,채용개진적고정시간창정단분비계발식규칙구해모형,정의잉여조작시간재[전치시간,배송준비시간]내적정단위긴급정단,구건종합고필긴급정도화상사도인소적재선정단분비산법。채용모배송중심14：00~18：00시간단내이박송분포（λ=17）수궤생성적정단진행수거실험,장실험결과여전통고정시간창재선정단분비산법진행비교。연구결과표명,고필완성기한시,계통간선배송적정단수량경다,총복무시간화평균유효정단복무시간경단,차출현연지정단적수량경소,연지시간경단。간선원공인수적증다재불동정도상제고배송솔,차고필완성기한시,배송솔제고폭도요대우전통산법;단수착인수적증가,배송솔적제고폭도정강저추세。
In the e-commerce on-line order picking system, customer orders＇ arrival time and goods cannot be informed in advance. With the constraints of picking equipment capacity and pickers＇ number, the order batching optimization approach, which focuses on the batehing time and batching strategy, is proposed to pick out maximum orders in the shortest service time before the due time. The on-line order batehing 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 （A = 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 different .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.