考虑托盘驻留期和订单快速响应的出入库策略研究

发布时间：2018-06-27 10:05

本文选题：自动化立体库 + 货位分配　；参考：《山东大学》2017年硕士论文

【摘要】：研究发现,在一个完整的仓储活动中,拣货过程是其中最费时费力的环节。拣货时间占整个仓储活动时间的35%左右,拣货成本大约占整个货物仓储成本的50%—60%。因此,提高拣货效率成为降低成本,提高配送中心运作效率的关键。要想提高拣货效率,可考虑从货物入库环节和拣货环节入手,做好货位的优化分配。本文从单个托盘在仓库中的驻留期入手进行货位分配的优化,以从而提高整个物流配送中心的运转效率,降低物流运作成本。对于仓库货位分配的优化问题,目前的研究大都是基于货物的出入库频率这种货物的整体属性来确定货位分配策略。本文首先将货位和托盘进行抽象化,并设置相应的参数,将单个货物托盘的周转率或者单个货物托盘在仓库里的驻留期(Duration of Stay,简称DOS)作为货位分配的依据,采用贪婪算法的基本思想,开发出基于贪婪算法的货位分配策略。又考虑到仓库在现实的操作环境中,市场需求不稳定,不同的时期各种货物的市场需求量会发生变化,不可能已知所有装载单元的到货量、需求量以及在仓库中驻留的时间,因此进一步引进基于渐消记忆离散灰色模型GM(1,1),通过各种货物的历史到货量和需求量来预测货物的实际需求量,由此获得入库装载单元在仓库中驻留的时间信息。做到各种货物在仓库各区域内相对均衡的分配,打破了传统的ABC分区的局限性,使储位分配更加灵活,更好的满足了客户订单随机性和多元化的特点。最后以某烟草配送中心的订单为例,通过MATLAB仿真软件验证所提方案的有效性。由此提高客户订单的响应速度,提高物流企业的服务水平,提高企业的市场竞争力。为缩短对客户订单的反应时间,本文考虑在离仓库I/O 口距离较近的位置预留出一块区域,称为货物应急区。在此区域内,通过分析仓库中各类货物的历史出库数量,按照相应的比例存放各类货物。当客户订单中包含的此种货物时,若客户要求的响应时间充足,则从仓库中相应的货位取货。如果接近客户要求的最晚出库时间,且货物的拣选还没有完成时,则考虑从货物应急区直接取货,在订单要求的最晚出库时间之前快速出库,完成订单的快速响应,满足客户需求。最后根据这个思路建立以订单响应时间为目标函数的数学模型。进一步研究在此种模式下的基于改进式遗传算法的货位分配策略,实现客户订单的快速响应。最后通MATLAB仿真软件,与传统的货位分配方法相比较,验证所提方案的有效性。
[Abstract]:It is found that the picking process is the most time-consuming and laborious part of a complete storage activity. Picking time accounts for about 35% of the total storage time, and picking cost accounts for about 50% of the total storage cost. Therefore, improving picking efficiency becomes the key to reduce cost and improve operation efficiency of distribution center. If we want to improve the efficiency of picking goods, we can start with the link of goods storage and picking, and do a good job of the optimal allocation of goods space. In order to improve the operation efficiency of the whole logistics distribution center and reduce the cost of logistics operation, this paper starts with the residence period of a single tray in the warehouse to optimize the distribution of goods. For the optimization of warehouse space allocation, most of the current research is based on the frequency of goods entering and out, which is the overall property of goods, to determine the allocation strategy. This paper firstly abstracts the goods and pallets, sets the corresponding parameters, and takes the turnover rate of the single cargo pallet or the duration of stay (DOS) of the single cargo pallet in the warehouse as the basis for the distribution of the cargo space. Using the basic idea of greedy algorithm, the allocation strategy of goods location based on greedy algorithm is developed. Considering also that in a realistic operating environment, market demand is unstable and that market demand for various goods varies at different times, and that it is not possible to know the quantity of arrival of all loading units, the demand and the length of stay in the warehouse, Therefore, a discrete grey model GM (1 ~ 1) based on fading memory is introduced to predict the actual demand of goods through the historical arrival and demand of various kinds of goods, and the time information of the storage unit staying in the warehouse is obtained. The distribution of all kinds of goods in warehouse areas is relatively balanced, which breaks the limitation of traditional ABC partition, makes storage allocation more flexible, and better meets the characteristics of randomness and diversification of customer orders. Finally, taking the order of a tobacco distribution center as an example, the effectiveness of the proposed scheme is verified by MATLAB simulation software. Therefore, the response speed of customer orders is improved, the service level of logistics enterprises is improved, and the market competitiveness of enterprises is improved. In order to shorten the response time to customer order, this paper considers reserving a region near the I / O port of warehouse, which is called cargo emergency zone. In this area, by analyzing the historical quantity of goods in warehouse, store all kinds of goods according to the corresponding proportion. When such goods are included in the customer's order, if the customer's response time is sufficient, the goods are taken from the corresponding location in the warehouse. If you are close to the latest delivery time required by the customer, and the picking of the goods has not yet been completed, then consider taking the goods directly from the cargo emergency area, and get out of the warehouse quickly before the latest delivery time required by the order, so as to complete the rapid response of the order. Meet customer needs. Finally, a mathematical model with order response time as the objective function is established according to this idea. This paper further studies the location allocation strategy based on improved genetic algorithm in this mode to realize the rapid response of customer orders. Finally, MATLAB simulation software is used to verify the effectiveness of the proposed scheme.
【学位授予单位】：山东大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：F274

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