A set-processing algorithm for scheduling staff on 4-day or 3-day work weeks

This paper presents an efficient algorithm for scheduling a single-category work force on 4-day or 3-day work weeks. Employees work 4 or 3 days each week, have A out of every B weekends off, and work no more than 5 consecutive days in a work stretch on 4-day work weeks and no more than 4 days in a work stretch on 3-day work weeks. Such conditions often prevail in 7-day-a-week organizations such as hospitals, manufacturing plants, and retail stores. We determine the minimum number of workers required to satisfy the scheduling constraints under any pattern of daily requirements. Then we present the algorithm for assigning days off for each worker, thereby determining the work schedules. We show that the algorithm, by construction, will necessarily satisfy the scheduling constraints. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 839–853, 1998     

基于神经网络信息融合技术的卫星定姿算法

姿态确定系统是卫星姿态控制系统中的重要组成部分,卫星姿态确定的精度直接影响卫星控制精度.为得到高姿态精度,针对由惯性测量单元(Inertial Measurement Unit),红外地平仪和太阳敏感器组成的卫星姿态确定系统,分别采用BP网络算法和径向基(RBF)网络算法对不同的姿态敏感器的输出数据进行融合,并用STK(Satellite Tool Kit)数据进行了仿真.仿真分析结果表明这两种学习算法均可以提高卫星定姿精度,相对而言,RBF网络无论是精度上还是收敛速度上均优于BP网络.     

Maintaining systems with heterogeneous spare parts

We consider the problem of optimally maintaining a stochastically degrading, single‐unit system using heterogeneous spares of varying quality. The system's failures are unannounced; therefore, it is inspected periodically to determine its status (functioning or failed). The system continues in operation until it is either preventively or correctively maintained. The available maintenance options include perfect repair, which restores the system to an as‐good‐as‐new condition, and replacement with a randomly selected unit from the supply of heterogeneous spares. The objective is to minimize the total expected discounted maintenance costs over an infinite time horizon. We formulate the problem using a mixed observability Markov decision process (MOMDP) model in which the system's age is observable but its quality must be inferred. We show, under suitable conditions, the monotonicity of the optimal value function in the belief about the system quality and establish conditions under which finite preventive maintenance thresholds exist. A detailed computational study reveals that the optimal policy encourages exploration when the system's quality is uncertain; the policy is more exploitive when the quality is highly certain. The study also demonstrates that substantial cost savings are achieved by utilizing our MOMDP‐based method as compared to more naïve methods of accounting for heterogeneous spares.     

A continuous-review inventory model with constant resupply time and defective items

As a result of imperfect production and inspection by suppliers, pilferage, and/or damage in transit, it is common that procurement orders may contain defective items. This article deals with a continuous-review inventory system with Poisson demand arrivals and constant resupply time. Items in resupply lots may not be of perfect quality. The operating characteristics of such a system are analyzed. For purposes of computational savings, an approximation scheme for the operating characteristics is presented. As a result of the approximation, the determination of the optimal ordering policy becomes much simpler. Extensive numerical tests suggest that the approximation scheme is very effective in giving the optimal or near-optimal ordering policies for such a system.     

Optimal maintenance policies for constantly monitored systems

A multistate system is assumed to be constantly monitored; i.e., the state of the system is always known with certainty. Damage to the system accumulates via a continuous-time Markov process. A model of the system including restoration costs and state occupation costs is developed. It is shown that under certain conditions the optimal restoration policy for the system is a control limit rule. A control limit rule is a policy which requires restoration of the system whenever the damage exceeds a certain level. Examples are presented to show that there are several situations in which, perhaps surprisingly, control limit rules are not optimal.     

Bounds and properties of the expected value of sample information for a project-selection problem

In this article we extend the work of Mehrez and Stulman [5] on the expected value of perfect information (EVPI) to the expected value of sample information (EVSI) for a class of economic problems dealing with the decision to reject or accept an investment project. It is shown that shifting the mean of the underlying a priori distribution of X, the project's monetary value from zero in either direction will decrease the associated EVSI of Y, the random sampled information. A theorem is then presented which gives an upper bound on the EVSI over all distributions of Y, as well as the structure of the posterior mean E[X|Y] for which this upper bound is achieved. Finally, the case where E[X|Y] is linear in Y is discussed and its performance compared with that of the optimal case.     

The impotence of conventional arms control: why do international regimes fail when they are most needed?

Amid tensions with the West over Ukraine, Russia pulled out of the Treaty on Conventional Armed Forces in Europe in March 2015. The Russian case is another example of a country disengaging from conventional arms control when relations with other member states deteriorate. This raises an important question: can arms control regimes aimed at preventing conflict survive periods of tension and preserve peace? This article argues no. It demonstrates that the prospect and stability of conventional arms control regimes depend on healthy international relations. In times of tension, governments rely on military institutions for advice and absorb military biases incompatible with arms control. Therefore, these regimes fail when most needed and are impotent as instruments of peace. Beyond conventional arms control, the article hints at the fragility of nuclear agreements such as the 2015 Iran deal and the 2010 New START between the United States and Russia.