Storage Assignment Optimization in a Multi-tier Shuttle Warehousing System

The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem（TSP）,which has been widely applied in the conventional automated storage and retrieval system（AS/RS）.However,the previous mathematical models in conventional AS/RS do not match multi-tier shuttle warehousing systems（MSWS） because the characteristics of parallel retrieval in multiple tiers and progressive vertical movement destroy the foundation of TSP.In this study,a two-stage open queuing network model in which shuttles and a lift are regarded as servers at different stages is proposed to analyze system performance in the terms of shuttle waiting period（SWP） and lift idle period（LIP） during transaction cycle time.A mean arrival time difference matrix for pairwise stock keeping units（SKUs） is presented to determine the mean waiting time and queue length to optimize the storage assignment problem on the basis of SKU correlation.The decomposition method is applied to analyze the interactions among outbound task time,SWP,and LIP.The ant colony clustering algorithm is designed to determine storage partitions using clustering items.In addition,goods are assigned for storage according to the rearranging permutation and the combination of storage partitions in a 2D plane.This combination is derived based on the analysis results of the queuing network model and on three basic principles.The storage assignment method and its entire optimization algorithm method as applied in a MSWS are verified through a practical engineering project conducted in the tobacco industry.The applying results show that the total SWP and LIP can be reduced effectively to improve the utilization rates of all devices and to increase the throughput of the distribution center.

Warehousing and OLAP Analysis of Bibliographic Data

In this paper, the system bgMath/OLAP for warehousing and online analytical processing bibliographic data is proposed. The implemented system can be useful for the users maintaining their electronic libraries with publications in order to monitoring, evaluating and comparing the scientific development of particular researchers, entire research groups, certain scientific fields and problems.

Qinhuangdao Bonded Warehousing Company

The Qinhuangdao Bonded Warehousing Company, approved by MOFTEC and the Customs Administration, is the only company handling bonded warehousing business in Hebei. Founded in 1992, the company owns RMB14.9369 million in assets, and has large-scale, modern bonded warehouses and two cooperative economic entities.

Discussion on the Application of Industry-Finance Integration in Warehousing Enterprises

In recent years,the transformation of warehousing enterprises has garnered widespread attention.The integration of industry and finance in management accounting can provide financial management support for the transformation of warehousing enterprises,deliver accurate and effective financial and business information,facilitate managers’decision-making,and achieve the benign development of enterprises.This paper discusses the problems in the application of industry-finance integration in warehousing enterprises,including the low degree of informatization,inefficient internal cost control,and mismatched staff quality,and then proposes corresponding measures,such as establishing and improving information systems,establishing a comprehensive budget management system,and establishing management measures for the integration of industry and finance in warehousing enterprises,so as to strengthen the application of industry-finance integration in warehousing enterprises.

Toward resilient cloud warehousing via a blockchain-enabled auction approach

Cloud warehousing service (CWS) has emerged as a promising third-party logistics service paradigm driven by the widespread use of e-commerce. The current CWS billing method is typically based on a fixed rate in a coarse-grained manner. This method cannot reflect the true service value under the fluctuating e-commerce logistics demand and is not conducive to CWS resilience management. Accordingly, a floating mechanism can be considered to introduce more flexible billing. A CWS provider lacks sufficient credibility to implement floating mechanisms because it has vested interests in terms of fictitious demand. To address this concern, this report proposes a blockchain-enabled floating billing management system as an overall solution for CWS providers to enhance the security, credibility, and transparency of CWS. A one-sided Vickrey–Clarke–Groves (O-VCG) auction mechanism model is designed as the underlying floating billing mechanism to reflect the real-time market value of fine-grained CWS resources. A blockchain-based floating billing prototype system is built as an experimental environment. Our results show that the O-VCG mechanism can effectively reflect the real-time market value of CWSs and increase the revenue of CWS providers. When the supply of CWS providers remains unchanged, allocation efficiency increases when demand increases. By analyzing the performance of the O-VCG auction and comparing it with that of the fixed-rate billing model, the proposed mechanism has more advantages. Moreover, our work provides novel managerial insights for CWS market stakeholders in terms of practical applications.

Knowledge Discovery in Data: A Case Study

It is common in industrial construction projects for data to be collected and discarded without being analyzed to extract useful knowledge. A proposed integrated methodology based on a five-step Knowledge Discovery in Data (KDD) model was developed to address this issue. The framework transfers existing multidimensional historical data from completed projects into useful knowledge for future projects. The model starts by understanding the problem domain, industrial construction projects. The second step is analyzing the problem data and its multiple dimensions. The target dataset is the labour resources data generated while managing industrial construction projects. The next step is developing the data collection model and prototype data ware-house. The data warehouse stores collected data in a ready-for-mining format and produces dynamic On Line Analytical Processing (OLAP) reports and graphs. Data was collected from a large western-Canadian structural steel fabricator to prove the applicability of the developed methodology. The proposed framework was applied to three different case studies to validate the applicability of the developed framework to real projects data.

Web Data Cube Construction in Multidimensional On-line Analytical Processing Environment

This paper investigates how to integrate Web data into a multidimensional data warehouse （cube） for comprehensive on-line analytical processing （OLAP） and decision making. An approach for Web data-based cube construction is proposed, which includes Web data modeling based on MIX （ Metadam based Integration model for data X-change ）, generic and specific mapping rules design, and a transformation algorithm for mapping Web data to a multidimensional array. Besides, the structure and implementation of the prototype of a Web data base cube are discussed.

Visual Composition of Complex Queries on an Integrative Genomic and Proteomic Data Warehouse

Biomedical questions are usually complex and regard several different life science aspects. Numerous valuable and he- terogeneous data are increasingly available to answer such questions. Yet, they are dispersedly stored and difficult to be queried comprehensively. We created a Genomic and Proteomic Data Warehouse (GPDW) that integrates data provided by some of the main bioinformatics databases. It adopts a modular integrated data schema and several metadata to describe the integrated data, their sources and their location in the GPDW. Here, we present the Web application that we developed to enable any user to easily compose queries, although complex, on all data integrated in the GPDW. It is publicly available at http://www.bioinformatics.dei.polimi.it/GPKB/. Through a visual interface, the user is only required to select the types of data to be included in the query and the conditions on their values to be retrieved. Then, the Web application leverages the metadata and modular schema of the GPDW to automatically compose an efficient SQL query, run it on the GPDW and show the extracted requested data, enriched with links to external data sources. Performed tests demonstrated efficiency and usability of the developed Web application, and showed its and GPDW relevance in supporting answering biomedical questions, also difficult.

The RFID-Based Manufacturing and Inventory Revolution

Radio frequency identification (RFID) is a contactless form of automatic identification and data capture (AIDC) technology. This paper explores the use of RFID in the new field of manufacturing automation and quality control. This paper consists of five parts. The first part gives a brief background and introduction of technology. The proposed use of RFID technology in the field of manufacturing automation and quality control is discussed in second part. The third part covers its use in the field of warehouse management system. Part four is a local review and analysis of RFID technology in manufacturing and warehousing which would support the potential use of this technology locally at China. The last part of paper gives concluding remarks about the RFID technology with recommendations of RFID use in these areas.

对数据仓库的认识

计算机技术的发展和各种新的需求，是数据仓库技术的产生的强大动力。数据仓库技术将从事事务处理的传统数据处理与具有分析特性的处理分离开来，使得数据仓库，结合数据库成为一个新的体系化环境。数据仓库，联机分析处理及数据挖掘构成了这一体系的三大技术，并且使得决策支持系统的真正实现成为可能。数据仓库和ＤＳＳ是密不可分的，利用了 ＤＷ技术的支持，企业的决策分析才更有真实的意义。

基于SSIS的商业智能平台设计与实现

首先提出在贵州省高速公路商业智能平台应用SSIS的意义,其次介绍SSIS;然后介绍了贵州省高速公路商业智能平台的整体设计;最后介绍基于SSIS的贵州省高速公路商业智能平台的实现。

Data-driven Distributed Analytics and Control Platform for Smart Grid Situational Awareness

A conceptual,data-driven framework for organizing the data analytics and control functions in an electrical distribution network is proposed in this paper.The framework is built such that it tightly corresponds to the naturally existing physical hierarchy of typical radial distribution networks,allowing for an organized and highly-localized set of data storage and analytics processes,which in turn correspond well to likely control commands.By utilizing this structure,the computational entities in the framework are endowed with persistent local situational awareness.However,the framework also permits,through a series of tiered communications,the operation of a centralized authority for overall system observability and controllability.

Database Research： Achievements and Challenges

Database system is the infrastructure of the modern information system. The R＆D in the database system and its technologies is one of the important research topics in the field. The database R＆D in China took off later but it moves along by giant steps. This report presents the achievements Renmin University of China （RUC） has made in the past 25 years and at the same time addresses some of the research projects we, RUC, are currently working on. The National Natural Science Foundation of China supports and initiates most of our research projects and these successfully conducted projects have produced fruitful results.

PMC： Select Materialized Cells in Data Cubes

QC-Tree is one of the most storage-efficient structures for data cubes in an MOLAP system. Although QC- Tree can achieve a high compression ratio, it is still a fully materialized data cube. In this paper, an improved structure PMC is presented allowing us to materialize only a part of the cells in a QC-Tree to save more storage space. There is a notable difference between our partially materialization algorithm and traditional materialized views selection algorithms. In a traditional algorithm, when a view is selected, all the cells in this view are to be materialized. Otherwise, if a view is not selected, all the cells in this view will not be materialized. This strategy results in the unstable query performance. The presented algorithm, however, selects and materializes data in cell level, and, along with further reduced space and update cost, it can ensure a stable query performance. A series of experiments are conducted on both synthetic and real data sets. The results show that PMC can further reduce storage space occupied by the data cube, and can shorten the time to update the cube.

Semi-Closed Cube： An Effective Approach to Trading Off Data Cube Size and Query Response Time

The results of data cube will occupy huge amount of disk space when the base table is of a large number of attributes. A new type of data cube, compact data cube like condensed cube and quotient cube, was proposed to solve the problem. It compresses data cube dramatically. However, its query cost is so high that it cannot be used in most applications. This paper introduces the semi-closed cube to reduce the size of data cube and achieve almost the same query response time as the data cube does. Semi-closed cube is a generalization of condensed cube and quotient cube and is constructed from a quotient cube. When the query cost of quotient cube is higher than a given threshold, semi-closed cube selects some views and picks a fellow for each of them. All the tuples of those views are materialized except those closed by their fellows. To find a tuple of those views, users only need to scan the view and its fellow. Thus, their query performance is improved. Experiments were conducted using a real-world data set. The results show that semi-closed cube is an effective approach of data cube.

An Adaptive Approach to Schema Classification for Data Warehouse Modeling

Data warehouse （DW） modeling is a complicated task, involving both knowledge of business processes and familiarity with operational information systems structure and behavior. Existing DW modeling techniques suffer from the following major drawbacks -- data-driven approach requires high levels of expertise and neglects the requirements of end users, while demand-driven approach lacks enterprise-wide vision and is regardless of existing models of underlying operational systems. In order to make up for those shortcomings, a method of classification of schema elements for DW modeling is proposed in this paper. We first put forward the vector space models for subjects and schema elements, then present an adaptive approach with self-tuning theory to construct context vectors of subjects, and finally classify the source schema elements into different subjects of the DW automatically. Benefited from the result of the schema elements classification, designers can model and construct a DW more easily.

Cache-Conscious Data Cube Computation on a Modern Processor

Data cube computation is an important problem in the field of data warehousing and OLAP （online analytical processing）. Although it has been studied extensively in the past, most of its algorithms are designed without considering CPU and cache behavior. In this paper, we first propose a cache-conscious cubing approach called CC-Cubing to efficiently compute data cubes on a modern processor. This method can enhance CPU and cache performances. It adopts an integrated depth-first and breadth-first partitioning order and partitions multiple dimensions simultaneously. The partitioning scheme improves the data spatial locality and increases the utilization of cache lines. Software prefetching techniques are then applied in the sorting phase to hide the expensive cache misses associated with data scans. In addition, a cache-aware method is used in CC-Cubing to switch the sort algorithm dynamically. Our performance study shows that CC-Cubing outperforms BUC, Star-Cubing and MM-Cubing in most cases. Then, in order to fully utilize an SMT （simultaneous multithreading） processor, we present a thread-based CC-Cubing-SMT method. This parallel method provides an improvement up to 27% for the single-threaded CC-Cubing algorithm.