一种数据仓库联机维护的集合刷新算法

提出了一种版本控制集合刷新算法（VSRA）.它采用增量维护、版本控制和批处理机制保证数据仓库的联机维护和数据一致性.VSRA不仅减少了数据库和数据仓库之间的通信流量,而且提高了实体化视图的刷新效率.用户可以随时使用VSRA进行联机分析处理,并能得到正确的结果.     

数据仓库中多视图环境下的联机维护

数据仓库的视图联机维护是指数数据仓库中的实体化视图实时地与信息源中的数据库仑保持一致,同时不影响前端用户对数据仓库的正常使用。为了解决多视图环境中视图联机维护与下钻查询的一致性问题,文中在数据仓库体系结构中引入了“基库”模型,并提出了相应的视图维护算法３ＶＰＡ。     

数据仓库联机维护中一致性问题的研究

数据仓库是存储供查询和决策分析用的集成化信息仓库,它的信息来源于不同地点的数据库或其他信息源.实体化视图是数据仓库中存储的主要信息实体,当原始数据发生变化时,数据仓库中的实体化视图也必须作相应的更新维护.在数据仓库实体化视图的联机维护过程中,由于联机分析处理（On-line Analytical Process,简称OLAP）查询的介入,会产生数据不一致的问题.文章提出了一种MVCA（multiversion compensating algorithm）算法来解决这一问题.MVCA采用版本控制方法,利用补偿思想和应答机制协调数据库和数据仓库之间的更新维护操作,达到保证数据一致的目的.最后,文章通过一个典型示例说明了该算法在实际中的具体应用.     

数据仓库联机维护技术的研究与实现

针对数据仓库联机维护技术提出了一种三层维护体系结构TMA,在其中引进了“数据仓库基库”概念,利用版本控制思想提出了对单视图和多视图的联机维护算法,并实现了一个原型验证系统。     

数据仓库的联机维护与下查

提出了一种三层数据仓库体系结构,引入了“数据仓库基库”概念,不权使得传统数据库能够更容易地融入数据仓库系统,而且增强了整个系统的伸缩性。在此基础上,提出了３ＶＷＱ（Ｔｈｒｅｅ－Ｖｅｒｓｉｏｎ Ｗｉｔｈｏｕｔ Ｑｕｉｅｓｃｉｎｇ）算法来解决数据仓库的联机维护问题及其对下查的支持。该算法采用版本控制和补偿思想来协调数据库和数据仓库之间的数据更新,从而保证了联机维护与下查的一致性。     

数据仓库中实化视图的联机维护分析

数据仓库中的信息是由各个独立分布的数据源的数据汇集而成，数据仓库中实化视图的联机维护是数据仓库系统维护的一项关键技术。本文通过例子说明了视图维护中会产生的数据不一致性问题，并详细分析了基于补偿、基于维护库和基于版本控制的三种视图维护方法。     

数据仓库视图一致性维护与下查研究

数据仓库是存储供查询和决策分析用的集成化信息仓库。实体化视图作为数据仓库中存储的主要信息实体,是由对上一级或外部数据源进行抽取、转化、传输和上载的数据构成的。当源数据发生变化时,如何进行数据仓库实体化视图的一致性维护以及OLAP查询,是一个有着实际意义的研究课题。论文提出的算法Glide采用版本控制、补偿思想和应答机制来协调源数据库与数据仓库间的数据更新,保证了数据仓库视图维护与下查的一致性,提高了算法的健壮程度和对源数据库端CPU的利用率,是以往同类算法的一个本质改进。论文指出算法Glide是完全一致的,并给出了严格的数学证明。文章还通过一个示例说明了该算法在实际中的具体运用。     

数据仓库,联机分析处理和联机分析开采研究

本文介绍了当前数据仓库系统的应用需求、基本特征、体系结构和构建技术;对传统的联机事务处理（ＯＬＴＰ）与联机分析处理（ＯＬＡＰ）进行了比较;分析了在数据仓库中实施ＯＬＡＰ使用的多维数据视图概念模型,同时介绍了建立在多维数据库（ＭＤＤ）上的ＭＯＬＡＰ,以及建立在星型（雪花）模型基础之上的ＲＯＬＡＰ两种联机分析技术,并对数据开采联机分析处理在数据仓库系统中的集成－联机分析开采（ＯＬＡＭ）进行了研究。     

一种数据仓库联机维护算法

数据仓库通常以离散的方式进行刷新,这样就不能向用户提供连接的查询服务。文章提出了一种适合数据仓库联机维护的算法－ＳＴＮＬ算法,它消除了２ＶＮＬ,ＭＶＮＬ等联机维护算法需要对元组暂时锁定的缺点,并且更容易实现。     

基于时间戳实化视图动态维护技术的研究

由于源数据的不稳定性,其结构和数据的变化必须及时传播到实体化视图中,以保持实体化视图与源数据变化的一致性,否则会降低实体化视图中数据的新鲜度,并影响OLAP查询结果的真实性和有效性.为此,本文提出了基于时间戳的动态视图维护技术.该技术采用版本链控制技术,通过时间戳的控制进一步使视图更新和查询的同步进行,有效地解决了由于OLTP更新事务和OLAP事务同时访问数据所发生冲突的问题,在满足视图联机实时维护的同时,更好的提高了数据仓库的新鲜度和OLAP的查询效率.     

扩展job shop模型的启发式批量流水线调度算法

提出了改进的job shop模型,定义了工作中心以及关键节点的概念。将流水线与批量调度策略引入到新的模型中,并在此基础上提出了一个关于扩展job shop模型的启发式批量流水线调度算法。在关键节点进行选择时,通过回溯计算其余产品的开始时间,使用贪心算法选择优先级最高的产品进行排序。该优先级法则由三个优先级变量组合而成,分别囊括了价值高低、时间紧要程度以及剩余加工时间这三个影响因素。进行加工时,设定最小加工批量,在一个工序内实现多套设备的并行加工,同时在两个相邻工序之间实现流水线加工,从而缩短加工时间,提高了生产效率。通过仿真表明该策略能取得较好的结果。     

Software tools for motif and pattern scanning: program descriptions including a universal sequence reading algorithm

Two programs, MOTIF and PATTERN, that scan sequences for matches to user-defined motifs and patterns of motifs based on identity and set membership are described. The programs use a simple and logical notation to define motifs, and may be used either interactively or by using command line parameters (suitable for batch processing). The two programs described also incorporate a simple, yet reliable, algorithm that automatically detects in which of six possible formats the sequence entry is written.     

A branch and price algorithm to minimize makespan on a single batch processing machine with non-identical job sizes

In this paper, we consider the scheduling problem on a single batch processing machine with non-identical job sizes; in which the machine has a limited capacity and can process a group of jobs simultaneously as a batch. The processing time of a batch is the longest processing time of all jobs in the batch. The objective is to minimize the makespan. We formulate the problem using Dantzig–Wolfe decomposition as a set partitioning problem. Based on the set partitioning formulation, we present a tight lower bound using column generation method. A heuristic algorithm is also developed to generate the basic solution in the column generation method. A branch and price algorithm which combines the column generation technique with branch and bound method is then presented to obtain the optimal solution of the problem. The efficiency of the proposed branch and price algorithm is ultimately compared to the branch and bound algorithm from the literature, based on the generated sample problems.     

Minimizing Mean Completion Time in a Batch Processing System

We consider batch processing jobs to minimize the mean completion time. A batch processing machine can handle up to $B$ jobs simultaneously. Each job is represented by an arrival time and a processing time. Jobs processed in a batch have the same completion time, i.e., their common starting time plus the processing time of their longest job. For batch processing, non-preemptive scheduling is usually required and we discuss this case. The batch processing problem reduces to the ordinary uniprocessor system scheduling problem if $B=1$. We focus on the other extreme case $B=+\infty$. Even for this seemingly simple extreme case, we are able to show that the problem is NP-hard for the weighted version. In addition, we establish a polynomial time algorithm for a special case when there are only a constant number of job processing times. Finally, we give a polynomial time approximation scheme for the general case.     

Scheduling semiconductor manufacturing processes to enhance system identification

Semiconductor manufacturing is characterized by a manufacturing line with multiple processing tools, products, and other sources of variation. Run-to-run control applications need a constant stream of information about the state of the process in order to perform well. The trace of the state error covariance matrix from the Kalman filter is used as a metric for determining the information content of a particular data set to the run-to-run control algorithm. Processing decisions such as batch scheduling, equipment allocation, and sampling plans are shown to have an effect on estimator performance. Algorithms using the state error covariance matrix are developed that can optimize the factory schedule in order to provide run-to-run control algorithms with the best possible information. Simulation results demonstrate that measurable improvements in state estimation and control output performance can be achieved by using information from the process estimator.     

Scheduling unrelated parallel batch processing machines with non-identical job sizes and unequal ready times

This research analyzes the problem of scheduling a set of n jobs with arbitrary job sizes and non-zero ready times on a set of m unrelated parallel batch processing machines so as to minimize the makespan. Unrelated parallel machine is a generalization of the identical parallel processing machines and is closer to real-world production systems. Each machine can accommodate and process several jobs simultaneously as a batch as long as the machine capacity is not exceeded. The batch processing time and the batch ready time are respectively equal to the largest processing time and the largest ready time among all the jobs in the batch. Motivated by the computational complexity and the practical relevance of the problem, we present several heuristics based on first-fit and best-fit earliest job ready time rules. We also present a mixed integer programming model for the problem and a lower bound to evaluate the quality of the heuristics. The small computational effort of deterministic heuristics, which is valuable in some practical applications, is also one of the reasons that motivates this study. The results show that the heuristic proposed in this paper has a superior performance compared to the heuristics based on ideas proposed in the literature.     

Single machine batch scheduling to minimize total completion time and resource consumption costs

In this paper we study the single-machine batch scheduling problem under batch availability, where both setup and job processing times are controllable by allocating a continuously divisible nonrenewable resource. Under batch availability a set of jobs is processed contiguously and completed together, when the processing of the last job in the batch is finished. We present polynomial time algorithms to find the job sequence, the partition of the job sequence into batches and the resource allocation, which minimize the total completion time or the total production cost (inventory plus resource costs).     

批处理机上具有两类释放时间的工件集竞争调度问题

研究了两个工件集合竞争在一台批处理机上加工的调度问题,其中每个集合的工件具有一个共同的释放时间.批处理机可以同时加工多个工件作为一批,每批的加工时间为该批工件中加工时间的最大值.基于两类释放时间的大小,针对无界批处理机上最小化一个集合工件的最大完工时间、最大延迟以及总完工时间,使得另一个集合工件的最大完工时间不超过给定上界问题,分别给出了最优求解方法.针对有界批处理机上最小化一个集合工件的最大完工时间,使得另一个集合工件的最大完工时间不超过给定上界问题,证明为一般意义NP-难问题,并给出伪多项式时间最优求解方法.