A Multi-stage Heuristic Algorithm for Matching Problem in the Modified Miniload Automated Storage and Retrieval System of E-commerce

E-commerce, as an emerging marketing mode, has attracted more and more attention and gradually changed the way of our life. However, the existing layout of distribution centers can＇t fulfill the storage and picking demands of e-commerce sufficiently. In this paper, a modified miniload automated storage/retrieval system is designed to fit these new characteristics of e-commerce in logistics. Meanwhile, a matching problem, concerning with the improvement of picking efficiency in new system, is studied in this paper. The problem is how to reduce the travelling distance of totes between aisles and picking stations. A multi-stage heuristic algorithm is proposed based on statement and model of this problem. The main idea of this algorithm is, with some heuristic strategies based on similarity coefficients, minimizing the transportations of items which can not arrive in the destination picking stations just through direct conveyors. The experimental results based on the cases generated by computers show that the average reduced rate of indirect transport times can reach 14.36% with the application of multi-stage heuristic algorithm. For the cases from a real e-commerce distribution center, the order processing time can be reduced from 11.20 h to 10.06 h with the help of the modified system and the proposed algorithm. In summary, this research proposed a modified system and a multi-stage heuristic algorithm that can reduce the travelling distance of totes effectively and improve the whole performance of e-commerce distribution center.

IOTA-Based Data Encryption Storage and Retrieval Method

At present,the traditional blockchain for data storage and retrieval reflects the characteristics of slow data uploading speed,high cost,and transparency,and there are a lot of corresponding problems,such as not supporting private data storage,large data operation costs,and not supporting Data field query.This paper proposes a method of data encryption storage and retrieval based on the IOTA distributed ledger,combined with the fast transaction processing speed and zero-value transactions of the IOTA blockchain,through the Masked Authenticated Messaging technology,so that the data is encrypted in the data stream.The form is stored in the distributed ledger,quickly retrieved through the field index mechanism established by the data form,and the data operation is carried out on the chain.Experimental results show that this system has high storage,encryption and retrieval performance,and good practicability.

X-RESTORE: Middleware for XML's Relational Storage and Retrieve

We propose a new approach to store and query XML data in an RDBMS basing on the idea of the numbering scheme and inverted list. O ur approach allows us to quickly determine the precedence, sibling and ancestor/ descendant relationships between any pair of nodes in the hierarchy of XML, and utilize path index to speed up calculating of path expressions. Examples have de monstrated that our approach can effectively and efficiently support both XQuery queries and keyword searches. Our approach is also flexible enough to support X ML documents both with Schema and without Schema, and applications both retrieva l and update. We also present the architecture of middleware for application acc essing XML documents stored in relations, and an algorithm translating a given X ML document into relations effectively.

DCRL-KG: Distributed Multi-Modal Knowledge Graph Retrieval Platform Based on Collaborative Representation Learning

The knowledge graph with relational abundant information has been widely used as the basic data support for the retrieval platforms.Image and text descriptions added to the knowledge graph enrich the node information,which accounts for the advantage of the multi-modal knowledge graph.In the field of cross-modal retrieval platforms,multi-modal knowledge graphs can help to improve retrieval accuracy and efficiency because of the abundant relational infor-mation provided by knowledge graphs.The representation learning method is sig-nificant to the application of multi-modal knowledge graphs.This paper proposes a distributed collaborative vector retrieval platform(DCRL-KG)using the multi-modal knowledge graph VisualSem as the foundation to achieve efficient and high-precision multimodal data retrieval.Firstly,use distributed technology to classify and store the data in the knowledge graph to improve retrieval efficiency.Secondly,this paper uses BabelNet to expand the knowledge graph through multi-ple filtering processes and increase the diversification of information.Finally,this paper builds a variety of retrieval models to achieve the fusion of retrieval results through linear combination methods to achieve high-precision language retrieval and image retrieval.The paper uses sentence retrieval and image retrieval experi-ments to prove that the platform can optimize the storage structure of the multi-modal knowledge graph and have good performance in multi-modal space.

Automatic Measurement and Control Design of Sea Wave Energy Storage and Seawater Desalination Device

The application of seawater desalination has become more and more popular. The reverse osmosis membrane method is one of its applications, but it consumes more energy resources and produces freshwater with high cost. The four-column floating bed we designed has low investment and is simple and easy to operate. The sea wave energy storage and seawater desalination device produced by this method has greatly reduced the cost of freshwater produced. This paper focuses on the design of the automatic measurement and control loop of the device.

The Complexity and On-Line Algorithm for Automated Storage and Retrieval System with Stacker Cranes on One Rail

This paper considers an on-line scheduling and routing problem concerning the automated storage and retrieval system from tobacco industry. In this problem, stacker cranes run on one common rail between two racks. Multiple input/output-points are located at the bottom of the racks. The stacker cranes transport bins between the input/output-points and cells on the racks to complete requests generated over time. Each request should be accomplished within its response time. The objective is to minimize the time by which all the generated requests are completed. Under a given physical layout, the authors study the complexity of the problem and design on-line algorithms for both one-stacker-crane model and two-stacker-crane model. The algorithms are validated by instances and numerical simulations.

An Approach for Content Retrieval from Web Pages Using Clustering Techniques

Mining the content from an information database provides challenging solutions to the industry experts and researchers, due to the overcrowded information in huge data. In web searching, the information retrieved is not an appropriate, because it gives ambiguous information for the user query, and the user cannot get relevant information within the stipulated time. To overcome these issues, we propose a new methodology for information retrieval EPCRR by providing the top most exact information to the user, by using the collaborative clustered automated filter which makes use of the collaborative data set and filter works on the prediction by providing the highest ranking for the exact data retrieved. The retrieval works on the basis of recommendation of data which consists of relevant data set with highest priority from the cluster of data which is on high usage. In this work, we make use of the automated wrapper which works similar to the meta crawler functionality and it obtains the content in the semantic usage data format. Obtained information from the user to the agent will be ranked based on the Enabled Pile clustered data with respect to the metadata information from the agent and end-user. The information is given to the end-user with the top most ranking data within the stipulated time and the remaining top information will be moved to the data repository for future use. The data collected will remain stable based on the user preference and works on the intelligence system approach in which the user can choose any information under any instances and can be provided with suitable high range of exact content. In this approach, we find that the proposed algorithm has produced better results than existing work and it costs less online computation time.

考虑能耗指标的双层自动化立体仓储系统布局研究

为解决仓储系统运行过程中能源消耗过大的问题,针对双层自动化立体仓库进行了能耗分析,建立了双层仓储系统存储、检索任务时间模型以及考虑物品自重的穿梭车(提升机、电梯)运动能耗模型,并利用仿真实验研究了仓库中自动小车及提升机的速度、加速度,货架布局对于仓库运行能耗、吞吐量的关系和影响。实验结果显示增加穿梭车速度、加速度都会提升系统吞吐量,速度对吞吐量的提升更大;增加电梯加速度、速度会适当降低能耗。达到吞吐量500条件下,新的系统布局可以降低20%左右的能耗并提升2.7%的吞吐量,帮助物流企业建立更加合理的仓库布局设计,从而减少存储和检索过程中的能源消耗。

自动化立体仓库退库货位优化问题及其求解算法

针对自动化立体仓库出库作业过程中剩余货物退库问题,以堆垛机作业总能耗最小化为目标,以退库货位分配为决策变量,建立了自动化立体仓库退库货位优化模型,提出了基于深度强化学习的自动化立体仓库退库货位优化框架。在该框架内,以立体仓库实时存储信息和出库作业信息构建多维状态,以退库货位选择构建动作,建立自动化立体仓库退库货位优化的马尔科夫决策过程模型;将立体仓库多维状态特征输入双层决斗网络,采用决斗双重深度Q网络(dueling double deep Q-network,D3QN)算法训练网络模型并预测退库动作目标价值,以确定智能体的最优行为策略。实验结果表明D3QN算法在求解大规模退库货位优化问题上具有较好的稳定性。

具有多层级货架的自动小车存取系统排队网建模与分析

为了满足多楼层生产车间之间的物料运输需求,同时减少企业成本,自动存取系统的设计问题变得愈发重要。带有多层级货架的自动小车存取系统因其优秀的吞吐能力和柔性,具有很好的应用前景。为了分析多层车间中带有多层级货架自动小车存取系统并行作业的性能,在分析自动导引小车(AGV)和电梯、伸缩臂作业方式的基础上,构建了半开排队网络模型,并设计了基于近似均值分析法的近似求解算法。该方法首先将半开排队网内部网络分为不同的单独网络模型,并分别重构为等效的闭排队网络模型。这些网络模型最终被聚合成一个节点,与外部的同步节点联合构建闭排队网络模型求解吞吐率。最后,针对内部网络的单独节点进行分析计算,得到其他系统性能指标。通过设计仿真实验,验证了所提方法的有效性和准确性。

基于3D穿梭车的活立方密集仓储系统及存取货调度研究

为满足新时代自动化密集仓储系统的需求,在保持高仓储密度的同时,也需重视系统的灵活性与高效性。因此,结合活立方密集仓储系统的多倍深存储和3D穿梭车仓储系统中的六向移动技术,提出以三维自主移动穿梭车为核心的活立方密集仓储系统。针对该系统中的存取货调度问题,建立了基于整数规划的三维网络流模型。为比较仓储密度相同时,包含提升机的传统活立方密集仓储系统与以三维自主移动穿梭车为核心的活立方密集仓储系统在存取货效率方面的性能,在不同系统配置下通过大量算例进行了数值实验,结果表明:以三维自主移动穿梭车为核心的活立方密集仓储系统在存取货时间上平均节省30%,系统效率有着较为显著的提高;模型在不同系统配置下均具有良好的求解性能,验证了三维网络流模型的有效性与通用性。

计算成像在全息存储相位恢复中的应用研究进展

全息存储技术作为一种三维体存储、二维面数据传输的数据存储技术,具有存储密度高、数据传输快等特点,是解决海量数据长期存储的有力方案之一。传统全息存储方法受到光电探测器只对强度响应的限制,通常采用纯振幅编码进行调制,但仅利用振幅信息无法完全发挥全息技术本身优势,如何简单快速、稳定精确地解码相位信息是全息存储技术面临的现实问题。计算成像因其算法多变、高感知维度等特点为全息存储技术的相位恢复问题提供了新的思路。本文主要从迭代计算相位恢复和深度学习相位重建角度回顾近年来利用计算成像技术解决全息存储相位恢复问题的一些工作,从存储密度提升、数据读取速度提升以及数据读取稳定性等角度对工作进行了分析,并对该方向未来发展做出展望。

V型三能级金刚石氮空位色心电磁诱导透明体系中孤子的存取

本文先构建一束弱探测场和一束强控制场所形成的V型三能级金刚石氮空位(NV)色心电磁诱导透明(EIT)模型,随后研究探测场在体系的线性吸收和非线性传播特性.结果表明,一旦开启强控制场,体系就会呈现出EIT窗口,且透明窗口的宽度随着控制场磁感应强度的增加而变宽.在非线性情况下,探测场能形成稳定传播的孤子,且可通过开启和关闭控制场的磁场实现孤子的存储和读取,可以有效地克服冷原子介质和量子点介质孤子存取的缺陷.值得一提的是,体系所存取孤子的振幅还可以通过控制场的磁感应强度来进行调节.

烟草行业自动化立体仓库的可视化盘点技术与方法研究

文章结合某烟草企业自动化立体仓库(Automated Storage/Retrieval Systems, AS/RS)存货盘点管理特点和实际需求,建立了一种基于图像回传方法与信息化技术的实施框架。在此基础上,设计了多种存货盘点模式以满足差异化的需求,并予以了实施和应用验证,为烟草行业AS/RS实现安全、高效、柔性和可追溯的存货盘点提供了一个有效的解决方案。最后,对图像自动识别技术在其中的应用进行了算法设计和可行性分析,为提升该行业AS/RS存货盘点的智能化水平提供了参考。

基于深度学习的货物盘点自动识别方法研究

文章针对自动化立体仓库(Automated Storage/Retrieval Systems,AS/RS)在高效及安全库存盘点、货物监控等方面的需求和存在的问题,提出了一种基于YOLOv3深度学习算法的货物异动及数量自动识别方法,并进行了算法实现。为验证该算法的有效性,文章以某烟草物流中心自动化立体仓库为对象进行了应用验证分析,结果表明该算法在经过小规模货物图像样本训练后即具备较高的识别能力,因此,采用该方法进行货物异动监控和数量自动识别具有较高的可行性和有效性。

大型LNG储罐三种高效自动化焊接工艺对比研究

我国建造储存绿色能源LNG用储罐单台已达27万m^(3),针对传统的SMAW焊接效率低、含有锰蒸汽和CO_(2)的烟尘等问题,采用热丝TIG,FCAW及MIG三种自动焊方法,进行了大量的试验研究,从而使LNG储罐的施焊环境大大改善,焊接效率及质量均大幅提升。结果表明,自动焊焊缝表面成形均远好于SMAW;焊接效率为MIG最高;焊接接头低温冲击韧性为热丝TIG最优。目前三种自动焊对现场组装精度要求均高于SMAW,热丝TIG对组装精度要求最高,因此尚需进一步提升自动化水平,以便在工程中大量推广应用。

基于电网分布式存储构建业务分析模型的探索和研究

由于电网大数据分散存储在不同的独立存储服务中,难以保证文档检索全面性和准确性,影响查询业务质量。为此,构建基于电网分布式存储的业务分析模型。切分待存储文件,组成文件碎片,分布存储到不同的存储节点中,构建电网分布式存储模型。针对该模型,扩展查询业务关键词,增大查询范围。基于查询业务扩展结果,构建业务探索分析模型,从分布式数据库中检索相关文档。实验结果表明:所构建模型的各类电网大数据检索F1值接近1,提高了电网分布式存储文档检索的全面性和准确性。

基于区块链的食品溯源存储检索方法应用研究

区块链在实际溯源场景中存在无法支撑大规模连续性数据高效存储的问题,且单一的数据查询方式无法满足应用需求,不利于溯源应用在多样化场景下的大规模落地。为探索溯源场景的高可拓展区块链存储引擎技术,通过基于数据连续性特点来优化数据存储、优化默克尔B+树结构、创建索引数据库等创新手段,实现了溯源数据区块链高效混合存储和高效数据检索,在食品安全溯源应用场景中提升了效率。

数字化藏书激光存贮检索信息类目映射方法

数字化藏书存贮检索受到信息映射影响,导致覆盖率与准确率值偏低,提出数字化藏书激光存贮检索信息类目映射方法。通过映射系统统计中图法和杜威十进分类法中的USMARC记录实例,构建类号映射关系,规范化处理中图法和DDC的数据,构造类目数据结构,划分检索数据表,抽取检索特征词;依据双序列比对,计算特征词、复合词汇类目和所处环境的相似度,实现数字化藏书激光存贮检索信息类目映射。实验结果表明,映射方法的覆盖率达到98.38%,准确率达到97.48%,该方法实现了覆盖率与准确率的双重提升。