An absolute approximation algorithm for scheduling unrelated machines

Non‐preemptive scheduling of n independent jobs on m unrelated machines so as to minimize the maximal job completion time is considered. A polynomial algorithm with the worst‐case absolute error of min{(1 ? 1/m)p_max, p} is presented, where p_max is the largest job processing time and p is the mth element from the non‐increasing list of job processing times. This is better than the earlier known best absolute error of p_max. The algorithm is based on the rounding of acyclic multiprocessor distributions. An O(nm²) algorithm for the construction of an acyclic multiprocessor distribution is also presented. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

A heuristic for maximizing the number of on‐time jobs on two uniform parallel machines

We consider the problem of maximizing the number of on‐time jobs on two uniform parallel machines. We show that a straightforward extension of an algorithm developed for the simpler two identical parallel machines problem yields a heuristic with a worst‐case ratio bound of at least . We then show that the infusion of a “look ahead” feature into the aforementioned algorithm results in a heuristic with the tight worst‐case ratio bound of , which, to our knowledge, is the tightest worst‐case ratio bound available for the problem. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

电磁振动给料机的研究与制造

利用振动原理,研究、设计、制造微型电磁振动给料机（筛）．设计了激磁铁芯、半波可控硅整流及控制电路．在对振动机械的隔振分析及优化设计理论的基础上,设计了整部机器的结构图纸,并制造了一部样机,给出了振动利用的一个范例．所研究制造的微型电磁振动机集机电为一体,在焊接、制药等诸多行业中具有广泛的应用价值．     

平面磨削精度控制的一种方法

分析了利用砂轮周边进行平面磨削加工产生形状误差的原因之一。即待加工表面的形状变化引起磨削力的变化,从而引起工艺系统的弹性变形的变化,这种变形最终导致工件产生形状误差。提出了解决这一问题的技术途径和方法,即将待加工表面分解成若干小块,对每一小块根据其形状进行分析,找出其磨削力的变化规律,然后用程序控制工件速度,从而保持磨削力近似不变,并总结了应用该方法的步骤。举例说明了应用该方法所取得的结果是:磨削平面的精度提高到原来的5倍,加工时间缩短到约为原来的一半。     

智能工具机的性能分析

本文论述了提高智能工具机性能所采取的技术措施,并对其性能进行了模拟。模拟结果表明,智能工具机的平均推理速度可达500KLIPS 左右,比日本的PSI—Ⅰ约快一倍,比美国加州大学Berkeley 分校研制的PLM 约快两倍。     

后勤保障指挥决策系统结构设计研究

军队后勤保障指挥决策系统是高技术局部战争后勤保障的中枢,科学合理构 建系统的结构是提高决策系统质量的关键,针对该系统大范围多领域的分布式特征,引入了 化学抽象机对系统结构进行形式化、规范化描述,可以清楚的反映系统的静态和动态特征, 对后勤"可视化"研究具有一定的指导意义。     

基于支持向量机的飞机备件需求预测

支持向量机是一种机器学习算法,在国外已广泛应用于工程实践领域。首先探讨了支持向量机回归预测模型的学习和预测机制,分析其中三个重要参数对算法的影响规律,得出一套定性的参数选择方法,然后将支持向量机引入到装备综合保障分析之中,构建了飞机备件智能预测模型,并对某型军用飞机备件需求进行了预测和分析,结果表明:基于支持向量机的备件需求预测是有效的、可行的。     

A note on combined job selection and sequencing problems

We investigate the solvability of two single‐machine scheduling problems when the objective is to identify among all job subsets with cardinality k,1≤k≤n, the one that has the minimum objective function value. For the single‐machine minimum maximum lateness problem, we conclude that the problem is solvable in O(n²) time using the proposed REMOVE algorithm. This algorithm can also be used as an alternative to Moore's algorithm to solve the minimum number of tardy jobs problem by actually solving the hierarchical problem in which the objective is to minimize the maximum lateness subject to the minimum number of tardy jobs. We then show that the REMOVE algorithm cannot be used to solve the general case of the single‐machine total‐weighted completion time problem; we derive sufficient conditions among the job parameters so that the total weighted completion time problem becomes solvable in O(n²) time. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 60: 449–453, 2013     

非周期不完全检测下的维修优化

针对gamma退化型单部件系统,基于更新和半更新过程理论建立了以期望费用率最小为目标的非周期不完全检测下的维修优化模型。利用检测规划函数使系统的检测间隔期可以依据系统的状态进行调整。为更加贴近实际,模型考虑了测量误差对维修优化的影响。通过计算可以得到最优预防性维修阈值和检测方案。给出了模型的应用算例,通过对退化速率和费用参数的灵敏度分析说明了模型的有效性。与不考虑检测误差的优化结果进行对比,证明了考虑检测误差的重要性。