Doubly Stochastic Sequential Assignment Problem

This article introduces the Doubly Stochastic Sequential Assignment Problem (DSSAP), an extension of the Sequential Stochastic Assignment Problem (SSAP), where sequentially arriving tasks are assigned to workers with random success rates. A given number of tasks arrive sequentially, each with a random value coming from a known distribution. On a task arrival, it must be assigned to one of the available workers, each with a random success rate coming from a known distribution. Optimal assignment policies are proposed for DSSAP under various assumptions on the random success rates. The optimal assignment algorithm for the general case of DSSAP, where workers have distinct success rate distribution, has an exponential running time. An approximation algorithm that achieves a fraction of the maximum total expected reward in a polynomial time is proposed. The results are illustrated by several numerical experiments. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 124–137, 2016     

Optimal staffing in nonstationary service centers with constraints

This paper considers optimal staffing in service centers. We construct models for profit and cost centers using dynamic rate queues. To allow for practical optimal controls, we approximate the queueing process using a Gaussian random variable with equal mean and variance. We then appeal to the Pontryagin's maximum principle to derive a closed form square root staffing (SRS) rule for optimal staffing. Unlike most traditional SRS formulas, the main parameter in our formula is not the probability of delay but rather a cost‐to‐benefit ratio that depends on the shadow price. We show that the delay experienced by customers can be interpreted in terms of this ratio. Throughout the article, we provide theoretical support of our analysis and conduct extensive numerical experiments to reinforce our findings. To this end, various scenarios are considered to evaluate the change in the staffing levels as the cost‐to‐benefit ratio changes. We also assess the change in the service grade and the effects of a service‐level agreement constraint. Our analysis indicates that the variation in the ratio of customer abandonment over service rate particularly influences staffing levels and can lead to drastically different policies between profit and cost service centers. Our main contribution is the introduction of new analysis and managerial insights into the nonstationary optimal staffing of service centers, especially when the objective is to maximize profitability. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 615–630, 2017     

Capacity expansion and cost efficiency improvement in the warehouse problem

The warehouse problem with deterministic production cost, selling prices, and demand was introduced in the 1950s and there is a renewed interest recently due to its applications in energy storage and arbitrage. In this paper, we consider two extensions of the warehouse problem and develop efficient computational algorithms for finding their optimal solutions. First, we consider a model where the firm can invest in capacity expansion projects for the warehouse while simultaneously making production and sales decisions in each period. We show that this problem can be solved with a computational complexity that is linear in the product of the length of the planning horizon and the number of capacity expansion projects. We then consider a problem in which the firm can invest to improve production cost efficiency while simultaneously making production and sales decisions in each period. The resulting optimization problem is non‐convex with integer decision variables. We show that, under some mild conditions on the cost data, the problem can be solved in linear computational time. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 367–373, 2016     

中低速磁浮列车传感器防浪涌设计及改进

为提高磁浮列车悬浮传感器的可靠性,分析在雷击、电源干扰等工况条件下的浪涌产生机理,确定浪涌冲击试验的内容,从通流量的角度说明已有防浪涌电路设计的可行性,并指出其在高温环境下在可靠性方面存在的不足。分别从降压和分流的角度进行分析,通过在原有电路中并接大容量电容的方式降低浪涌对敏感器件的冲击,从而提高传感器电源的抗浪涌冲击能力。     

无线传感器网络信息质量评估的柔性框架

为建立完整统一的无线传感器网络信息质量评估体系,提出可灵活剪裁的柔性框架来动态地评估无线传感器网络应用中信息的准确性和时效性。该框架基于信息融合理论和时间刻度标记技术,在sink节点聚合网络中所有传感器节点的信息。将信息融合结果近似为真值,利用观测信息与融合结果的数值或语义差异分别评估测量数据和决策信息的准确性。根据信息获取的截止期限和延迟敏感性,分三类描述和建模信息时效性,并通过轻量级的信息获取时间测量法量化。采用滑动窗口机制和增量计算方法,动态地更新评估结果。通过仿真三个目标监测应用场景的信息时效性评估和两个环境监测应用场景的信息准确性评估验证了框架的有效性。仿真结果与信息质量参考基准吻合,表明该框架能够灵活地评估不同无线传感器网络应用中信息的准确性和时效性。     

基于圆柱体缺陷构件的超声探伤重构研究

圆柱体构件中非轴对称人造缺陷偏心圆孔的超声探伤一直是无损检测的难点。基于脉冲反射原理设计超声实验平台,根据检测回波信号判定偏心圆孔缺陷所呈现的特征。在实验研究基础上,针对声场在圆柱体工件内部的传播情况,根据惠更斯原理以圆柱体为发射声源,基于k-wave仿真工具箱建立仿真平台,并利用声学传感器接收声波信号,设计的仿真平台能够实现360°同时刻采集工件的发射信号,同时利用传播过程中声压强弱的变化构建声场模型。根据采集的信号采用逆时反演重构模型,直观可视化地重构了内部缺陷的位置形状信息。     

基于Riccati方程的动态传感器分配算法

针对组网跟踪系统传感器分配算法计算量过大的问题,提出了一种基于Riccati方程的动态传感器分配算法。该算法通过Riccati方程离线计算各传感器组合跟踪下的稳态滤波协方差,根据稳态滤波协方差与期望协方差的接近程度动态分配传感器资源。仿真结果显示,与传统协方差控制和贪婪算法相比,基于Riccati方程的动态传感器分配算法在大大减少计算量的同时能够保持较好的跟踪性能。该方法能够更好地应用于大规模传感器组网目标协同跟踪系统。     

基于节点剩余能量的分时分簇LEACH改进算法

针对无线传感网络中高效路由协议的设计问题,基于传感器节点的剩余能量提出一种分时分簇的改进LEACH算法。算法通过分时分簇方式,有效克服了传统LEACH算法中簇首数目不稳定的缺陷,且不会额外增加网络的能耗,使得簇首在整个网络中的分布以及网络的能量消耗更加均衡,有效延长了传感器网络的正常工作时间。仿真实验验证了改进算法的有效性。     

相控阵雷达LPI搜索方法研究

相控阵雷达可通过合理配置工作参数优化其性能。针对相控阵雷达在搜索目标时易受敌方电子侦察设备威胁的现实,研究了在保持搜索能力的同时,通过合理配置参数降低截获概率的问题。分析了影响相控阵雷达搜索状态LPI(Low Probability of Intercept)性能的主要因素,建立了截获概率模型与搜索能力模型,给出了3种参数调整策略。仿真试验验证了模型的有效性,并比较了3种策略的优劣。     

基于动态可调簇的能量感知无线传感网数据收集协议

针对无线传感网中高效数据收集和传输的需要,提出了一种基于动态可调簇的能量感知数据收集协议ACEDGP(Adjusted Cluster-based energy-aware Data Gathering Protocol)。该协议初始时根据区域将节点等分成许多簇结构,簇首节点负责簇内部数据的收集和聚合,距离较远的簇通过其他簇首节点的转发实现数据的收集;随着时间的推移和节点能量的减少,ACEDGP能够统计各簇首能量消耗预测簇的通信频次,根据动态调整簇策略选择合适的簇首节点和合并分裂各个相邻的簇,保证各簇首节点簇内数据收集和簇间数据转发的能量平衡。仿真结果表明,与典型的分簇协议相比,ACEDGP能够更好地平衡节点的能耗,获得更长的网络生存期。