Query Optimization in Multidatabase Systems

Global query execution in a multidatabase system can be done parallelly, as all the local databases are independent. In this paper, a cost model that considers parallel execution of subqueries for a global query is developed. In order to obtain maximum parallelism in query execution, it is required to find a query execution plan that is represented in the form of a bushy tree and this query tree should be balanced to the maximal possible extent with respect to execution time. A new bottom up approach called Agglomerative Approach (AA) is proposed to construct balanced bushy trees with respect to execution time. By the deterministic nature of this approach, it generates local optimal solutions. This local minima problem will be severe in the case of graph queries, i.e., queries that are represented with a graph structure. A Simulated annealing Approach (SA) is employed to obtain a (near) optimal solution. These approaches (AA and SA) are suitable for handling on-line and off-line queries respectively. A Hybrid Approach (HA), that is an integration of AA and SA, is proposed to optimize queries for which the estimated time to be spent on optimization is known a priori. Results obtained with AA and SA on both tree and graph structured queries are presented.     

高纯金属与聚合物膜pH电极的研制

介绍以纯金属为基体,PVC为载体,α-萘胺为活性物质,三氯甲烷为溶剂研制成的聚合物膜电极,将它用于测定溶液的pH,取得了一些成效。     

Sep: A Fixed Degree Regular Network for Massively Parallel Systems

We propose a family of regular Cayley network graphs of degree three based on permutation groups for design of massively parallel systems. These graphs are shown to be based on the shuffle exchange operations, to have logarithmic diameter in the number of vertices, and to be maximally fault tolerant. We investigate different algebraic properties of these networks (including fault tolerance) and propose a simple routing algorithm. These graphs are shown to be able to efficiently simulate or embed other permutation group based graphs; thus they seem to be very attractive for VLSI implementation and for applications requiring bounded number of I/O ports as well as to run existing applications for other permutation group based network architectures.     

Modeling rolling batch planning as vehicle routing problem with time windows

This paper considers the rolling batch planning problem of grouping and sequencing a given set of slabs into several rolling units in iron and steel industry. The existing mathematical methods often used for the problem are traveling salesman problem (TSP) and vehicle routing problem (VRP), but these methods are not precise, because the position limitation of some slabs in a rolling unit scheduling is not considered. Therefore we suggest a new model, vehicle routing problem with time window (VRPTW) to describe the rolling batch planning problem, in which the position limitation of slabs are quantified as the time constraints. Several solution methods including the genetic algorithm are presented for solving the problem and the computational results show that the genetic algorithm is superior to other methods.In this paper, the vehicle routing problem with time window (VRPTW) of combinational optimization is used to analyze and model the rolling batch planning problem. Genetic algorithm and heuristic are used to solve the problem. Simulation results based on the actual production data show that this model is precise and the genetic algorithm based method is very promising.     

An investigation of mating and population maintenance strategies in hybrid genetic heuristics for product line designs

This research builds on prior work on developing near optimal solutions to the product line design problems within the conjoint analysis framework. In this research, we investigate and compare different genetic algorithm operators; in particular, we examine systematically the impact of employing alternative population maintenance strategies and mutation techniques within our problem context. Two alternative population maintenance methods, that we term “Emigration” and “Malthusian” strategies, are deployed to govern how individual product lines in one generation are carried over to the next generation. We also allow for two different types of reproduction methods termed “Equal Opportunity” in which the parents to be paired for mating are selected with equal opportunity and a second based on always choosing the best string in the current generation as one of the parents which is referred to as the “Queen bee”, while the other parent is randomly selected from the set of parent strings. We also look at the impact of integrating the artificial intelligence approach with a traditional optimization approach by seeding the GA with solutions obtained from a Dynamic Programming heuristic proposed by others. A detailed statistical analysis is also carried out to determine the impact of various problem and technique aspects on multiple measures of performance through means of a Monte Carlo simulation study. Our results indicate that such proposed procedures are able to provide multiple “good” solutions. This provides more flexibility for the decision makers as they now have the opportunity to select from a number of very good product lines. The results obtained using our approaches are encouraging, with statistically significant improvements averaging 5% or more, when compared to the traditional benchmark of the heuristic dynamic programming technique.     

分布式个人文件系统的设计与实现

提出了一种基于E-mail系统的分布式文件系统——EMDFS,给出了扩展的STMP协议(ESTMP)的状态转换方式和定义,在此基础上研究了利用ESMTP来构建分布式个人文件系统的方法和模型,设计了EMDFS的模型、内外存的结构、I/O操作、用户接口以及EMDFS的各种功能。     

多核环境下Hilbert曲线划分简单要素多边形合并算法

为了解决大规模复杂多边形数据合并运算效率问题,减少在空间数据库中检索多边形时的磁盘读取次数,针对多核环境下简单要素类多边形合并的特点,利用Hilbert曲线划分方法对简单要素的多边形进行空间数据划分,利用多核处理器并发执行,充分利用了多核计算环境中CPU的计算能力,保证了合理的任务分配与充分利用。介绍了该算法中用到的简单要素类多边形合并算子,利用对重合边的判断来进行多边形的合并;最后对提出的算法进行了实验分析。实验证明,本算法在进行大数据的多边形集合合并时效率较高,基于本算法开发的功能用于实际问题中可较好地解决大规模复杂多边形数据层合并运算的效率问题。     

简单多边形方向及顶点凹凸性的快速判定

基于简单多边形方向与顶点凹凸性的内在联系，采用极值点性质判定多边形方向，通过多边形顶点坐标判定其拓扑映射点之间的位置关系，结合以上两方面对顶点的凹凸性作出判断。对基于拓扑映射的多边形顶点凹凸判别算法作出有效的改进，避免了原算法申大量的重复计算。实践证明，有效的减少计算次数，提高了效率。     

简单多边形顶点凸凹性的快速确定算法

本文深入剖析了平面简单多边形方向（逆时针或顺时针）与顶点凸凹性的内在本质联系，提出了确定顶点凸凹性的快速算法，并解决了根据凸点确定多边形方向的基本问题。本文方法已应用于工厂设计软件ＰＤＳＯＦＴ的工厂模型消隐和平剖图消隐中，实践证明效果很好。     

Concurrent optimal allocation of distributed manufacturing resources using extended Teaching-Learning-Based Optimization

The optimal allocation of distributed manufacturing resources is a challenging task for supply chain deployment in the current competitive and dynamic manufacturing environments, and is characterised by multiple objectives including time, cost, quality and risk that require simultaneous considerations. This paper presents an improved variant of the Teaching-Learning-Based Optimisation (TLBO) algorithm to concurrently evaluate, select and sequence the candidate distributed manufacturing resources allocated to subtasks comprising the supply chain, while dealing with the trade-offs among multiple objectives. Several algorithm-specific improvements are suggested to extend the standard form of TLBO algorithm, which is only well suited for the one-dimensional continuous numerical optimisation problem well, to solve the two-dimensional (i.e. both resource selection and resource sequencing) discrete combinatorial optimisation problem for concurrent allocation of distributed manufacturing resources through a focused trade-off within the constrained set of Pareto optimal solutions. The experimental simulation results showed that the proposed approach can obtain a better manufacturing resource allocation plan than the current standard meta-heuristic algorithms such as Genetic Algorithm, Particle Swarm Optimisation and Harmony Search. Moreover, a near optimal resource allocation plan can be obtained with linear algorithmic complexity as the problem scale increases greatly.