基于RFID技术的数字化仓储的研究

发布时间：2018-01-20 15:49

本文关键词： 动态分配仓储系统周转率 RFID 交叉变异函数局部最优　出处：《浙江理工大学》2017年硕士论文　论文类型：学位论文

【摘要】：仓储是企业生产和销售之间的重要桥梁,现代化高效率的数字化仓储系统的关键在于提高仓库的利用率、减少货物盘点耗时以及优化货位的分配。优化后的货位分配策略能够有效的提高仓库的周转率,从而使得企业从生产到销售运转的更加流畅,使客户满意度提高。本文对结合RFID技术的现代化仓储进行研究,首先对RFID进行科学合理的设计与部署来解决传统仓库对货物出入库时数据上报及查对困难,耗时又容易出错的不足。重新设计划分仓库库区,有效地提高仓库的利用率,大大地降低了货位处于空闲的时间。其次,构建货物出入库动态货位分配数学模型,通过对相应算法进行改进来解决货位分配问题。具体研究如下:1.针对传统仓库对出入库货物信息采取人工或半自动化录入,耗费极大的时间又容易出现偏差的问题,在仓储系统中引进RFID技术实现数据的自动采集。根据库内空间进行科学布局,对于划分到具体的货位进行RFID部署设计。设计采用在每个货位中心位置安装了地埋式电子标签的方式,真正做到数字化货位管理。RFID电子标签采用地埋式设计,有效地解决了以往电子标签在货物表面容易损坏、污染、脱落、干扰的问题,保证了数据读取的高效性、准确性。2.RFID天线的设计与部署对整个RFID系统性能产生很大的影响。RFID电子标签与天线之间因极化方式不同,会出现标签天线与阅读器天线极化方向匹配失衡的情况。有时RFID天线的部署方式不合理产生部分信号丢失问题。本文采用了一种圆极化RFID天线的设计方式,对天线进行了科学合理的部署设计,有效地解决了数据读取失败的问题,同时也改善了RFID读取时部分信号丢失的情况。3.针对传统入库货位分配策略不能有效的满足如今货物存取量大、存取频繁和存储货位要求动态变化的难题,本文提出了一种基于改进遗传算法的动态货位分配策略,该策略解决的是多目标优化的问题。对于入库货位动态分配问题需要综合考虑货位的分配涉及到的出库时间最短、货物同一原则,以及不同时间段货物周转率的变化等因素。在寻优过程中通过对种群均值的分析,动态地对遗传算法的交叉率和变异率进行调整而得到最优解。这种在算法迭代的过程中动态地调整交叉变异算子大小的策略能够很好地改善算法搜寻时易陷入早熟的不足,最终找到最优的分配货位。4.为了使货物能够及时高效的运送转移到达客户手里,对在途车辆实时定位跟踪有重要的意义。实时跟踪不仅可以对在途货物进行实时监控,而且也利于提高仓储作业效率。通过集成企业GPS系统和GIS系统,开发动态物流服务平台,实现对货物运输动态管理。
[Abstract]:Storage is an important bridge between enterprise production and sales. The key of modern and efficient digital storage system is to improve the utilization ratio of warehouse. The optimized allocation strategy can effectively improve the turnover of the warehouse and make the enterprise from production to sales operation more smooth. To improve customer satisfaction. This paper studies the modern warehousing combined with RFID technology. First of all, the scientific and reasonable design and deployment of RFID is carried out to solve the difficulties of data reporting and checking in and out of the warehouse of traditional warehouse, which is time-consuming and error prone. Effectively improve the utilization rate of warehouse, greatly reduce the free time. Secondly, build the mathematical model of the dynamic allocation of goods into and out of storage. Through the improvement of the corresponding algorithm to solve the problem of cargo allocation. The specific research is as follows: 1. For the traditional warehouse to store goods information manual or semi-automatic input. It is very time-consuming and prone to the problem of deviation. The RFID technology is introduced into the storage system to realize the automatic data collection. According to the space in the warehouse, the scientific layout is carried out. The RFID deployment design is carried out for the specific cargo locations. The design adopts the method of installing buried electronic tags at the center of each cargo location. Truly achieve digital cargo management. RFID electronic label using buried design, effectively solve the former electronic labels on the surface of goods easily damaged, pollution, fall off, interference. Ensure the high efficiency of data reading. 2. The accuracy of the design and deployment of RFID antenna has a great impact on the performance of the whole RFID system. The polarization between RFID tags and antennas is different. The mismatch of the polarization direction of tag antenna and reader antenna will occur. Sometimes the problem of partial signal loss is caused by the unreasonable deployment of RFID antenna. A circular polarized RFID antenna is designed in this paper. The way. The antenna is designed scientifically and reasonably, which effectively solves the problem of data reading failure. At the same time, it also improves the situation of partial signal loss when RFID reads. 3. The traditional allocation strategy can not effectively meet the large quantity of goods access. This paper presents a dynamic location allocation strategy based on improved genetic algorithm. The strategy solves the problem of multi-objective optimization. For the dynamic allocation of cargo spaces, it is necessary to consider the shortest outgoing time involved in the allocation of cargo spaces and the same principle of goods. As well as the change of goods turnover rate in different time periods. Through the analysis of the mean value of the population in the process of optimization. The optimal solution is obtained by dynamically adjusting the crossover rate and mutation rate of genetic algorithm. This strategy of dynamically adjusting the size of crossover mutation operator in the iterative process of the algorithm can improve the algorithm searching easily early. Undercooked. Finally find the optimal distribution of goods. 4. In order to enable the timely and efficient transfer of goods to the customer. Real-time tracking of vehicles in transit is of great significance. Real-time tracking can not only monitor goods in transit, but also improve the efficiency of warehousing. By integrating enterprise GPS system and GIS system. Develop dynamic logistics service platform to realize the dynamic management of cargo transportation.
【学位授予单位】：浙江理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP391.44

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