Value management of diagnostic equipment with cancelation,no‐show,and emergency patients

Magnetic resonance imaging and other multifunctional diagnostic facilities, which are considered as scarce resources of hospitals, typically provide services to patients with different medical needs. This article examines the admission policies during the appointment management of such facilities. We consider two categories of patients: regular patients who are scheduled in advance through an appointment system and emergency patients with randomly generated demands during the workday that must be served as soon as possible. According to the actual medical needs of patients, regular patients are segmented into multiple classes with different cancelation rates, no‐show probabilities, unit value contributions, and average service times. Management makes admission decisions on whether or not to accept a service request from a regular patient during the booking horizon to improve the overall value that could be generated during the workday. The decisions should be made by considering the cancelation and no‐show behavior of booked patients as well as the emergency patients that would have to be served because any overtime service would lead to higher costs. We studied the optimal admission decision using a continuous‐time discrete‐state dynamic programming model. Identifying an optimal policy for this discrete model is analytically intractable and numerically inefficient because the state is multidimensional and infinite. We propose to study a deterministic counterpart of the problem (i.e., the fluid control problem) and to develop a time‐based fluid policy that is shown to be asymptotically optimal for large‐scale problems. Furthermore, we propose to adopt a mixed fluid policy that is developed based on the information obtained from the fluid control problem. Numerical experiments demonstrate that this improved policy works effectively for small‐scale problems. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 287–304, 2016     

面向多核网络分组处理系统的线程亲和缓冲区管理机制

基于通用多核架构的网络分组处理系统性能受到诸如分组IO开销高、多核共享内存及进程调度竞争大、页表缓冲表项失效率高等问题的困扰。为此提出一种基于通用多核网络分组处理系统、面向高速分组转发应用的线程亲和缓冲区硬件管理机制,并在网络专用协处理引擎上实现。该机制采用无中断的线程亲和调度策略,将包含控制信息与缓冲区地址信息的描述符和分组数据按照分组处理的线程号链式地对应加载在多个地址连续的共享缓冲区中。基于通用多核和现场可编程门阵列平台进行报文转发测试,实验结果表明,采用线程亲和缓冲区管理机制能使平均报文转发处理性能提升12.4%,有效地降低IO开销和TLB表项失效率。     

消防部队火灾扑救和应急救援心理训练实践与探索

消防部队承担着复杂而危险的火灾扑救和应急救援任务,战斗中常会出现各种不良心理,心理素质是影响部队战斗力的重要因素。开展心理素质训练,提高消防官兵心理素质和心理适应能力是一个亟待解决的问题。阐述了消防部队火灾扑救和应急救援工作实际以及有关心理学知识,研究如何开展火灾扑救和应急救援心理训练,提高消防官兵的心理素质和心理适应能力。     

伪劣消防产品现状及整治对策探讨

消防水带、消防水枪、消火栓箱体、室内消火栓、钢质防火门、应急照明、疏散指示标志、灭火器等多种消防产品,不合格产品很多,存在问题严重。分析了假冒伪劣消防产品的现状,并分析了存在问题的原因,从联合治理、提高执法人员素质、健全法规制度、加大宣传力度等方面提出了整治假冒伪劣消防产品的措施,指出了在具体工作中遇到的难题。     

以科学发展观为牵引实现学员队科学管理

军队院校学员队应坚持以培养人才为中心,坚持理论与实际、学院教育与部队建设相结合,遵循院校教育规律,坚持“解放思想、勇于创新,需求牵引、强化特色,遵循规律、持续发展,突出重点、整体推进,注重质量、讲求效益”的原则,全面推进创新教育和素质教育;加强科学管理、创新管理、从严管理,切实提高学员综合素质。     

转变管理模式注重学员创造性思维能力的培养

学员队管理要注重学员创造性思维能力的培养。在分析传统管理模式对学员创造性思维能力培养的制约因素的基础上,提出了管理者应转变管理模式,注重培养学员创造性思维能力的几最思考。     

基于贝叶斯决策方法的项目管理能力评估研究

项目管理能力是评价科研单位是否具有牵头组织能力的重要指标之一。针对现有评价方法在稳定性、科学性方面的不足,以传统的科研项目管理能力评估方法为基础,引入贝叶斯理论,建立了贝叶斯决策评估模型,并利用实际案例验证了其在科研项目管理能力评估中的有效性。结果表明,该评估方法能够充分利用历史资料和专家意见,对初步评估结果进行再度评估,具有较强的客观性、准确性。     

不同初速弹丸对靶板的损伤仿真与评估

为了研究弹丸对武器装备的损伤,建立弹丸侵彻多层靶板的有限元模型,对不同初速弹丸侵彻多层靶板进行仿真试验,引入等效应变及等效应力参量以精确描述靶板损伤,提出一种基于多元统计分析对靶板损伤进行评估的方法。结果表明：利用该方法所得到的计算结果与理论分析结果完全一致。这说明基于多元统计分析的靶板损伤评估方法能够正确地评价仿真实验中目标靶板的战损程度,因而可以进一步应用于装备侵彻损伤评估与易损性研究中。     

风险评价在军队营区环境管理中的应用

分析了军队营区环境风险的概念,认为要消减军队营区环境风险,不能仅考虑降低风险概率或风险后果,而应从风险概率与风险后果两者的乘积效应出发,通过综合分析和控制环境风险系统来解决;着重探讨了军队营区环境风险评价的内容和方法,包括环境风险识别、环境风险预计、环境风险评价与对策.军队营区环境风险评价可从二个层次进行评价一是从事件及与之有关联的周围环境条件出发,按"环境风险系统"的思路,从风险源、初级控制条件、二级控制条件、目标4个阶段进行评价;二是从事件或行动的具体问题出发,评价其风险的重大性和可接受性.最后讨论了军队营区环境风险管理的内容和方法.     

Managing components for assemble‐to‐order products with lead‐time‐dependent pricing: The full‐shipment model

We study a component inventory planning problem in an assemble‐to‐order environment faced by many contract manufacturers in which both quick delivery and efficient management of component inventory are crucial for the manufacturers to achieve profitability in a highly competitive market. Extending a recent study in a similar problem setting by the same authors, we analyze an optimization model for determining the optimal component stocking decision for a contract manufacturer facing an uncertain future demand, where product price depends on the delivery times. In contrast to our earlier work, this paper considers the situation where the contract manufacturer needs to deliver the full order quantity in one single shipment. This delivery requirement is appropriate for many industries, such as the garment and toy industries, where the economies of scale in transportation is essential. We develop efficient solution procedures for solving this optimization problem. We use our model results to illustrate how the different model parameters affect the optimal solution. We also compare the results under this full‐shipment model with those from our earlier work that allows for multiple partial shipments. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007