带时间窗的J公司仓储出库作业人员排班优化问题研究

发布时间：2018-02-21 14:55

本文关键词： 出库排班优化订单成本　出处：《北京交通大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着消费者日趋理性,电商行业的整体发展从野蛮增长过渡到稳中有升,"节流"成为电商增加利润的重要途径。J公司作为国内最大的自营式电商企业,自有物流体系是其高效配送服务的保障,但也造成了巨大的成本负担。加强成本控制是J公司可持续发展的必要途径。由于J公司的订单量是随时间动态变化的,随着大数据的应用,单量的预测可以精准到小时。随着自动化仓储设施的引进,库内的作业流程越来越规范,仓库需要精益化生产来提高效率,降低成本。本文通过调研发现,J公司仓储的出库作业存在人员的空闲时间较多、作业人员的每小时人效差异大以及订单积压量大等问题。因此J公司需要精细化的排班,来提高订单的完成率、减少人力成本浪费。本文通过对J公司出库作业人员排班的影响因素进行分析,结合J公司仓储出库作业的实际情况,将总成本分为不能完成波次清零要求的惩罚成本和人员空闲时间造成的浪费的人力成本两部分,以总成本最小为目标,建立了优化模型,并采用近邻域搜索算法,求出各个出库作业环节工作人员的班次及人数。最后通过实地调查与数据搜集,以J公司某品类仓为例,利用实际生产数据对模型进行求解验证,并对结果进行效果分析和讨论,证明模型的有效性和实用性。以往研究的排程问题多是静态调度问题,在已知生产任务的前提下,如何将有效的资源优化配置,合理安排生产作业,以在一定的时间内完成生产任务。本文研究对象是电商企业,订单是随时间动态变化的,因此本文的研究对于订单波动下的排班问题有一定借鉴意义。图10幅,表18个,参考文献40篇。
[Abstract]:As consumers become more and more rational, the overall development of e-commerce industry has shifted from savage growth to steady growth. "cutting costs" has become an important way for e-commerce to increase profits. J Company is the largest self-owned e-commerce enterprise in China. The self-owned logistics system is the guarantee of its efficient distribution service, but it also causes a huge cost burden. Strengthening cost control is the necessary way for J Company to develop continuously. Because the order quantity of J Company changes with time, With the application of big data, the single prediction can be accurate to the hour. With the introduction of automated storage facilities, the working process in the warehouse is becoming more and more standardized, and the warehouse needs lean production to improve efficiency. In this paper, we find out that there are many problems such as more idle time of the workers, the large difference in the efficiency per hour and the large backlog of orders in the out-of-store operation of company J. Therefore, company J needs to schedule the shift carefully. In order to improve the completion rate of orders and reduce the waste of labor costs. Through the analysis of the factors affecting the scheduling of the workers in J Company, combined with the actual situation of the warehouse and out of the warehouse of J Company, The total cost is divided into two parts: the penalty cost which can not fulfill the wave zero requirement and the manpower cost caused by the waste of staff idle time. The optimization model is established with the aim of minimum total cost, and the nearest neighbor domain search algorithm is adopted. Finally, through field investigation and data collection, taking a category warehouse of company J as an example, the model is solved and verified by actual production data. The results are analyzed and discussed to prove the validity and practicability of the model. The scheduling problems studied in the past are mostly static scheduling problems. In order to complete the production task in a certain time, the research object of this paper is the e-commerce enterprise, and the order changes with the time. Therefore, the study of this paper has some reference significance for the scheduling problem under the fluctuation of orders. 10 figures, 18 tables and 40 references.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F724.6;F272.92

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