Sojourn times in G/M/1 fork‐join networks

We consider a processing network in which jobs arrive at a fork‐node according to a renewal process. Each job requires the completion of m tasks, which are instantaneously assigned by the fork‐node to m task‐processing nodes that operate like G/M/1 queueing stations. The job is completed when all of its m tasks are finished. The sojourn time (or response time) of a job in this G/M/1 fork‐join network is the total time it takes to complete the m tasks. Our main result is a closed‐form approximation of the sojourn‐time distribution of a job that arrives in equilibrium. This is obtained by the use of bounds, properties of D/M/1 and M/M/1 fork‐join networks, and exploratory simulations. Statistical tests show that our approximation distributions are good fits for the sojourn‐time distributions obtained from simulations. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Bayesian enhanced decision making for deteriorating repairable systems with preventive maintenance

Since a system and its components usually deteriorate with age, preventive maintenance (PM) is often performed to restore or keep the function of a system in a good state. Furthermore, PM is capable of improving the health condition of the system and thus prolongs its effective age. There has been a vast amount of research to find optimal PM policies for deteriorating repairable systems. However, such decisions involve numerous uncertainties and the analyses are typically difficult to perform because of the scarcity of data. It is therefore important to make use of all information in an efficient way. In this article, a Bayesian decision model is developed to determine the optimal number of PM actions for systems which are maintained according to a periodic PM policy. A non‐homogeneous Poisson process with a power law failure intensity is used to describe the deteriorating behavior of the repairable system. It is assumed that the status of the system after a PM is somewhere between as good as new for a perfect repair and as good as old for a minimal repair, and for failures between two preventive maintenances, the system undergoes minimal repairs. Finally, a numerical example is given and the results of the proposed approach are discussed after performing sensitivity analysis. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

农村公共财政政策下的消防工作研究

介绍了农村消防工作与农村公共财政政策的内在联系,分析了农村公共财政政策和农村消防基础设施建设存在问题。就改革农村公共财政政策,加强农村消防基础设施建设进行了探讨。     

Steady‐state diffusion approximations for discrete‐time queue in hospital inpatient flow management

In this article, we analyze a discrete‐time queue that is motivated from studying hospital inpatient flow management, where the customer count process captures the midnight inpatient census. The stationary distribution of the customer count has no explicit form and is difficult to compute in certain parameter regimes. Using the Stein's method framework, we identify a continuous random variable to approximate the steady‐state customer count. The continuous random variable corresponds to the stationary distribution of a diffusion process with state‐dependent diffusion coefficients. We characterize the error bounds of this approximation under a variety of system load conditions—from lightly loaded to heavily loaded. We also identify the critical role that the service rate plays in the convergence rate of the error bounds. We perform extensive numerical experiments to support the theoretical findings and to demonstrate the approximation quality. In particular, we show that our approximation performs better than those based on constant diffusion coefficients when the number of servers is small, which is relevant to decision making in a single hospital ward.     

基于Citespace的国内公共政策研究现状分析

推进社会经济发展和管理需要科学制定和实施公共政策对当前研究现状进行分析梳理,有利于该领域的发展,使公共政策的制定和执行更加科学有效。以CNKI数据库收录的5799篇国内公共政策研究期刊论文为样本,采用文献计量法和知识可视化分析工具CiteSpace,对国内公共政策研究的现状、演进与热点等进行深入探讨。结果表明,21世纪以来,公共政策研究进入了高潮,但作者、机构之间学术联系较弱,还处于比较分散的状态。研究热点主要集中在政策制定、合法性有效性评估、群众认可及产业应用方面,新的研究前沿将是开拓民主渠道、完善监督机制、推动政府决策科学化等方面。     

Epidemics,national security,and US immigration policy

What are relationships between epidemics, national security, and US immigration policy? This question is important because it sheds light on transnational or nontraditional security areas, American immigration policy, and a pressing issue for US leaders who have recently faced epidemics such as the West Africa Ebola outbreak that began in 2013. This article answers it and lays ground in the area by reviewing epidemics in world history, using International Relations and Security Studies works to specify dangers of contagions for states, and identifying three general immigration measures that American leaders have utilized from the seventeenth century to the present day to protect against contagions, which are (1) policies restricting entrance of foreigners thought to carry specified diseases, (2) the isolation or quarantining of immigrants with contagious disease, and (3) delegating the President with authority to stop immigration in the event of an epidemic abroad. This study has implications for research and contemporary US immigration policy.     

The limits of robotic solutions to human challenges in the land domain

In the face of rapid technological change and the creation of ambitious military modernisation programmes, this paper argues that land forces, in managing the relationship between force levels and the adoption of military robotics, must recognise that there are inherent limits to techno-centric force reduction efforts and realise the inefficacy of substituting skilled soldiers with robots. It begins with an overview of how the proper integration of robotics into a military’s force structure can improve capability, save lives and potentially reduce costs, but suggests that common accounts of robot utility are exaggerated and endanger the risk assessment processes governing the adoption of said technologies and relevant personnel settings. The paper explores the limits of robotic solutions to military problems, discussing their technical limitations, redundancy and related issues that, when combined with a technico-moral skills degradation problem also detailed within, point to the need to reshape force structures to suit the adoption of robotics while preserving existing levels of human staffing.     

Single‐commodity stochastic network design under demand and topological uncertainties with insufficient data

Stochastic network design is fundamental to transportation and logistic problems in practice, yet faces new modeling and computational challenges resulted from heterogeneous sources of uncertainties and their unknown distributions given limited data. In this article, we design arcs in a network to optimize the cost of single‐commodity flows under random demand and arc disruptions. We minimize the network design cost plus cost associated with network performance under uncertainty evaluated by two schemes. The first scheme restricts demand and arc capacities in budgeted uncertainty sets and minimizes the worst‐case cost of supply generation and network flows for any possible realizations. The second scheme generates a finite set of samples from statistical information (e.g., moments) of data and minimizes the expected cost of supplies and flows, for which we bound the worst‐case cost using budgeted uncertainty sets. We develop cutting‐plane algorithms for solving the mixed‐integer nonlinear programming reformulations of the problem under the two schemes. We compare the computational efficacy of different approaches and analyze the results by testing diverse instances of random and real‐world networks. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 154–173, 2017     

Many‐server loss models with non‐poisson time‐varying arrivals

This article proposes an approximation for the blocking probability in a many‐server loss model with a non‐Poisson time‐varying arrival process and flexible staffing (number of servers) and shows that it can be used to set staffing levels to stabilize the time‐varying blocking probability at a target level. Because the blocking probabilities necessarily change dramatically after each staffing change, we randomize the time of each staffing change about the planned time. We apply simulation to show that (i) the blocking probabilities cannot be stabilized without some form of randomization, (ii) the new staffing algorithm with randomiation can stabilize blocking probabilities at target levels and (iii) the required staffing can be quite different when the Poisson assumption is dropped. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 177–202, 2017     

Statistical analysis for masked system life data from Marshall‐Olkin Weibull distribution under progressive hybrid censoring

This paper considers the statistical analysis of masked data in a series system, where the components are assumed to have Marshall‐Olkin Weibull distribution. Based on type‐I progressive hybrid censored and masked data, we derive the maximum likelihood estimates, approximate confidence intervals, and bootstrap confidence intervals of unknown parameters. As the maximum likelihood estimate does not exist for small sample size, Gibbs sampling is used to obtain the Bayesian estimates and Monte Carlo method is employed to construct the credible intervals based on Jefferys prior with partial information. Numerical simulations are performed to compare the performances of the proposed methods and one data set is analyzed.