Scheduling maintenance and semiresumable jobs on a single machine

The majority of scheduling literature assumes that the machines are available at all times. In this paper, we study single machine scheduling problems where the machine maintenance must be performed within certain intervals and hence the machine is not available during the maintenance periods. We also assume that if a job is not processed to completion before the machine is stopped for maintenance, an additional setup is necessary when the processing is resumed. Our purpose is to schedule the maintenance and jobs to minimize some performance measures. The objective functions that we consider are minimizing the total weighted job completion times and minimizing the maximum lateness. In both cases, maintenance must be performed within a fixed period T, and the time for the maintenance is a decision variable. In this paper, we study two scenarios concerning the planning horizon. First, we show that, when the planning horizon is long in relation to T, the problem with either objective function is NP-complete, and we present pseudopolynomial time dynamic programming algorithms for both objective functions. In the second scenario, the planning horizon is short in relation to T. However, part of the period T may have elapsed before we schedule any jobs in this planning horizon, and the remaining time before the maintenance is shorter than the current planning horizon. Hence we must schedule one maintenance in this planning horizon. We show that the problem of minimizing the total weighted completion times in this scenario is NP-complete, while the shortest processing time (SPT) rule and the earliest due date (EDD) rule are optimal for the total completion time problem and the maximum lateness problem respectively. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 845–863, 1999     

Scheduling and lot streaming in two‐machine open shops with no‐wait in process

We study the problem of minimizing the makespan in no‐wait two‐machine open shops producing multiple products using lot streaming. In no‐wait open shop scheduling, sublot sizes are necessarily consistent; i.e., they remain the same over all machines. This intractable problem requires finding sublot sizes, a product sequence for each machine, and a machine sequence for each product. We develop a dynamic programming algorithm to generate all the dominant schedule profiles for each product that are required to formulate the open shop problem as a generalized traveling salesman problem. This problem is equivalent to a classical traveling salesman problem with a pseudopolynomial number of cities. We develop and test a computationally efficient heuristic for the open shop problem. Our results indicate that solutions can quickly be found for two machine open shops with up to 50 products. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

抢险救灾工程破碎机械保障效能评估

破碎作业是抢险救灾工程保障的重要内容.以抗震救灾工程机械抢险作业理论与实践为基础,运用层次分析法构建了工程破碎机械保障效能评价指标体系,探索了相应的评价方法,并应用于工程保障实践.实践表明,该方法有利于抢险救灾科学决策,对合理选配工程机械,提高突发事件工程保障效能具有积极的促进作用.     

逼近理想灰关联投影多目标决策的点迹-航迹关联算法

点迹-航迹数据关联是多目标跟踪的重要组成部分。将多目标决策思想和灰关联分析方法引入点迹-航迹关联的研究,提出了一种基于逼近理想灰关联投影多目标决策的点迹-航迹数据关联算法。仿真实验表明,该算法在密集多目标情况下有一定的实际应用价值。     

A misclassification cost‐minimizing evolutionary–neural classification approach

Machine learning algorithms that incorporate misclassification costs have recently received considerable attention. In this paper, we use the principles of evolution to develop and test an evolutionary/genetic algorithm (GA)‐based neural approach that incorporates asymmetric Type I and Type II error costs. Using simulated, real‐world medical and financial data sets, we compare the results of the proposed approach with other statistical, mathematical, and machine learning approaches, which include statistical linear discriminant analysis, back‐propagation artificial neural network, integrated cost preference‐based linear mathematical programming‐based minimize squared deviations, linear integrated cost preference‐based GA, decision trees (C 5.0, and CART), and inexpensive classification with expensive tests algorithm. Our results indicate that the proposed approach incorporating asymmetric error costs results in equal or lower holdout sample misclassification cost when compared with the other statistical, mathematical, and machine learning misclassification cost‐minimizing approaches. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006.     

基于LabVIEW的电机数据采集系统

介绍了基于LabVIEW的电机数据采集系统的硬件组成和软件设计,提出了在LabVIEW下高速连续采集及存盘技术的实现方法,以及自动搜索基波频率的谐波分析方法,还分析了循环采样方式造成的各采样通道之间的相对相位误差产生的原因,提出采用分组采样方式减小这种误差,并给出了部分程序.最后给出了部分试验结果,证明所提方法的正确性.     

基于程序状态变迁的ASLR机制脆弱性分析方法

地址随机化ASLR是一种针对控制流劫持漏洞的防御机制。已有的漏洞自动分析与利用技术缺少对地址随机化机制影响的分析,导致生成的测试用例在实际环境中的运行效果受到极大限制。针对地址随机化的缺陷及其绕过技术的特点,本文提出了一种地址随机化脆弱性分析方法。该方法使用有限状态机描述程序运行路径中各关键节点的状态;针对常见的内存泄漏与控制流劫持场景建立约束条件;通过求解内存泄露状态约束与控制流劫持状态约束的兼容性,分析地址随机化机制在特定场景下的脆弱性。实验结果显示,该方法可有效检测通过内存泄漏导致的地址随机化绕过及控制流劫持攻击,实现自动化的地址随机化脆弱性分析,提高针对软件安全性分析的效率。     

异步电机定子电阻的观测

介绍了一种基于神经网络技术的感应电机定子电阻观测方法;讨论了定子电阻样本规划,并设计训练形成了定子电阻神经网络观测器.试验表明,该技术方法能有效地实施定子绕组电阻在线观测.     

基于扩展状态机的资源泄漏检测方法

基于扩展状态机对资源泄漏故障进行描述,给出了资源泄漏缺陷状态机,定义了缺陷的状态、状态迁移图和状态转换表。设计和实现了资源泄漏检测算法。该算法在对控制流进行遍历的过程中,按照资源泄漏缺陷状态机给出的转换条件进行状态计算,如果计算结果为故障,则报告1个资源泄漏故障。应用该算法对大型开源软件进行测试,发现多个资源泄漏故障。测试结果表明：该算法具有测试效率高和误报率低等特点。     

“电机统一理论”在电机控制中的作用

直流电机在恒速时其电压方程为常系数的线性微分方程,在电机控制中能进行快速的转矩和磁通控制。而异步电机是一个多变量、强耦合、非线性的时变参数系统,很难直接通过外加信号准确控制电磁转矩。但若以转子磁通这一旋转的空间矢量为参考坐标,应用"电机统一理论",利用从静止坐标系到旋转坐标系之间的变换,则可以把定子电流中的励磁电流分量与转矩电流分量变成标量独立开来,进行分别控制。这样,通过坐标变换重建的电机模型就可等效为一台直流电机,从而可像直流电机那样进行快速的转矩和磁通控制,给电机控制系统带来新的契机。