分布式流体系结构及其编程模型与资源管理

利用互联网资源提供大数据计算服务面临着资源异构性、动态性与通信长延迟等方面的挑战,现有分布式计算模型仍存在一些不足。运用流计算模型提出分布式流体系结构,包括分布式流编程模型与资源管理等,能够高效支持多种并行执行模式。在10个CPU-GPU异构结点上实现了原型系统,仿真实验验证了7个不同的测试用例。实验结果表明,与本地串行计算相比,分布式流体系结构可以平均提高39倍计算性能,具有较大的应用潜力。     

电力市场环境下发电厂机组检修计划

分析了传统的统一调度下和电力市场环境下发电厂机组检修计划的不同,在此基础上提出不同于以往的检修计划方法。以检修费用、电价收益损失和违约金之和最小为目标函数,然后采用0-1整数规划的直接枚举法求解。最后通过算例论证了该方法的可行性。     

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     

A comparative study of three tool replacement/operation sequencing strategies in a flexible manufacturing system

This paper studies three tool replacement/operation sequencing strategies for a flexible manufacturing system over a finite time horizon: (1) failure replacement—replace the tool only upon failure, (2) optimal preventive tool replacement for a fixed sequence of operations, and (3) joint scheduling of the optimal preventive tool replacement times and the optimal sequence of operations. Stochastic dynamic decision models are used for strategies 2 and 3. The optimization criterion for strategies 2 and 3 is the minimization of the total expected cost over the finite time horizon. We will show through numerical studies that, with the same amount of information, the total expected costs can be reduced considerably by choosing an optimal strategy. Our conclusion is that in flexible manufacturing, optimal tool replacement and optimal operations sequencing are not separate issues. They should be considered jointly to minimize the expected total cost. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 479–499, 2000     

对潜搜索的灰色整数规划模型

在对潜搜索中,针对搜索兵力武器装备战技性能的优劣、指挥人员的军政素质的高低、水文气象条件的好坏等因素均会随着时间的推移而发生变化的特点,为了取得最佳的搜潜效果,需要根据时间变化给不同的作战单元分派不同的作战任务.将整数规划与灰色模型相结合,建立了对潜搜索的灰色整数规划模型,给出了检验方法和求解步骤,并举例分析说明.经验证,该模型精度等级较高,且能使各作战单元的搜索效率达到最佳,因此,可资对潜搜索兵力分配时借鉴.     

弹炮混编防空群兵力分配模型

针对对付现代日益发展的空袭手段的一种有效方法--弹炮混编防空布势中存在的防空武器种类繁多,兵力分配复杂,难以充分发挥各自效能的问题,建立了非线性规划模型,利用动态规划对该模型进行分析,运用拉格朗日降维法进行降维,将三维降为二维.经防空作战的实例验证该算法不但能将两维降到单维,而且还可以将多维降到单维,能节省计算机的内存使用率,提高仿真计算的速度,符合信息化条件下指挥决策实时化的要求且分配效果较好.     

Orbix的分布对象计算性能分析

通过一个计数器的分布对象设计及Orbix实现,阐明了先进的分布对象技术标准CORBA的核心概念以及符合CORBA2．0标准的中间件产品Orbix的分布对象设计和实现过程,通过计算比较并分析了Orbix在单机和网络分布环境下实现效率的差异,并提出了用单机模拟网络环境下分布对象实现效率的方法．     

The parallel replacement problem with demand and capital budgeting constraints

A generalized parallel replacement problem is considered with both fixed and variable replacement costs, capital budgeting, and demand constraints. The demand constraints specify that a number of assets, which may vary over time, are required each period over a finite horizon. A deterministic, integer programming formulation is presented as replacement decisions must be integer. However, the linear programming relaxation is shown to have integer extreme points if the economies of scale binary variables are fixed. This allows for the efficient computation of large parallel replacement problems as only a limited number of 0–1 variables are required. Examples are presented to provide insight into replacement rules, such as the “no‐splitting‐rule” from previous research, under various demand scenarios. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 40–56, 2000     

Optimal nonmyopic gambling strategy for the generalized Kelly criterion

We consider the optimal wagers to be made by a gambler who starts with a given initial wealth. The gambler faces a sequence of two-outcome games, i.e., “win” vs. “lose,” and wishes to maximize the expected value of his terminal utility. It has been shown by Kelly, Bellman, and others that if the terminal utility is of the form log x, where x is the terminal wealth, then the optimal policy is myopic, i.e., the optimal wager is always to bet a constant fraction of the wealth provided that the probability of winning exceeds the probability of losing. In this paper we provide a critique of the simple logarithmic assumption for the utility of terminal wealth and solve the problem with a more general utility function. We show that in the general case, the optimal policy is not myopic, and we provide analytic expressions for optimal wager decisions in terms of the problem parameters. We also provide conditions under which the optimal policy reduces to the simple myopic case. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44: 639–654, 1997     

Inventory policies for a make‐to‐order system with a perishable component and fixed ordering cost

We consider a make‐to‐order production system where two major components, one nonperishable (referred to as part 1) and one perishable (part 2), are needed to fulfill a customer order. In each period, replenishment decisions for both parts need to be made jointly before demand is realized and a fixed ordering cost is incurred for the nonperishable part. We show that a simple (s_n,S,S) policy is optimal. Under this policy, S along with the number of backorders at the beginning of a period if any and the availability of the nonperishable part (part 1) determines the optimal order quantity of the perishable part (part 2), while (s_n,S) guide when and how much of part 1 to order at each state. Numerical study demonstrates that the benefits of using the joint replenishment policy can be substantial, especially when the unit costs are high and/or the profit margin is low. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009