Probabilistic resource pooling games

We study a setting with a single type of resource and with several players, each associated with a single resource (of this type). Unavailability of these resources comes unexpectedly and with player‐specific costs. Players can cooperate by reallocating the available resources to the ones that need the resources most and let those who suffer the least absorb all the costs. We address the cost savings allocation problem with concepts of cooperative game theory. In particular, we formulate a probabilistic resource pooling game and study them on various properties. We show that these games are not necessarily convex, do have non‐empty cores, and are totally balanced. The latter two are shown via an interesting relationship with Böhm‐Bawerk horse market games. Next, we present an intuitive class of allocation rules for which the resulting allocations are core members and study an allocation rule within this class of allocation rules with an appealing fairness property. Finally, we show that our results can be applied to a spare parts pooling situation.     

北斗卫星伪距信号质量评估及偏差校正

针对北斗卫星信号存在系统性伪距偏差的问题,从多路径角度评估北斗三频信号的质量,验证了该项偏差与卫星轨道类型、卫星仰角及信号频率有关。为消除这一系统性偏差的影响,采用连续分段线性函数建立北斗三频伪距偏差校正模型。与现有的改正模型所不同,所提模型不仅采用了更长时间范围内的北斗实测数据,更为重要的是它顾及了改正数的精度信息。基于动态精密单点定位的实验结果表明,采用所提方法修正后,接收机定位性能有明显提升。     

基于LBP-PCA的多传感器目标识别算法

为了更加有效地提高多传感器图像融合后的识别率,提出一种基于LBP-PCA的多传感器目标识别算法。首先分别对红外和可见光图像进行预处理用以突显出要识别的目标,采用LBP算法提取目标的特征点向量,利用PCA算法进行特征融合,得到降维后的融合特征,最后利用SVM(支持向量机)进行分类和识别。实验仿真结果表明多传感器目标经过LBP-PCA融合后在保持足够数量的有效信息基础上降低了特征的维数,有效地提高了目标识别率。     

一种基于部分搜索的GNSS模糊度解算方法

为解决LAMBDA算法搜索策略效率不高的问题,提出了一种基于部分搜索的模糊度解算新方法。该方法的解算成功率接近LAMBDA算法,且只需对最后3维模糊度元素采取搜索策略。同时,通过合理设定搜索椭球的大小和搜索策略;大大提高了搜索效率。通过实验对该新算法与Bootraping算法、LAMBDA算法进行了比较分析,进一步验证了该新算法的有效性。     

Single batch machine scheduling with deliveries

We consider the problem of scheduling a set of n jobs on a single batch machine, where several jobs can be processed simultaneously. Each job j has a processing time p_j and a size s_j. All jobs are available for processing at time 0. The batch machine has a capacity D. Several jobs can be batched together and processed simultaneously, provided that the total size of the jobs in the batch does not exceed D. The processing time of a batch is the largest processing time among all jobs in the batch. There is a single vehicle available for delivery of the finished products to the customer, and the vehicle has capacity K. We assume that K = rD, where and r is an integer. The travel time of the vehicle is T; that is, T is the time from the manufacturer to the customer. Our goal is to find a schedule of the jobs and a delivery plan so that the service span is minimized, where the service span is the time that the last job is delivered to the customer. We show that if the jobs have identical sizes, then we can find a schedule and delivery plan in time such that the service span is minimum. If the jobs have identical processing times, then we can find a schedule and delivery plan in time such that the service span is asymptotically at most 11/9 times the optimal service span. When the jobs have arbitrary processing times and arbitrary sizes, then we can find a schedule and delivery plan in time such that the service span is asymptotically at most twice the optimal service span. We also derive upper bounds of the absolute worst‐case ratios in both cases. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 470–482, 2015     

Model parameter estimation and residual life prediction for a partially observable failing system

We consider a partially observable degrading system subject to condition monitoring and random failure. The system's condition is categorized into one of three states: a healthy state, a warning state, and a failure state. Only the failure state is observable. While the system is operational, vector data that is stochastically related to the system state is obtained through condition monitoring at regular sampling epochs. The state process evolution follows a hidden semi‐Markov model (HSMM) and Erlang distribution is used for modeling the system's sojourn time in each of its operational states. The Expectation‐maximization (EM) algorithm is applied to estimate the state and observation parameters of the HSMM. Explicit formulas for several important quantities for the system residual life estimation such as the conditional reliability function and the mean residual life are derived in terms of the posterior probability that the system is in the warning state. Numerical examples are presented to demonstrate the applicability of the estimation procedure and failure prediction method. A comparison results with hidden Markov modeling are provided to illustrate the effectiveness of the proposed model. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 190–205, 2015     

A sequential scheduling problem with impatient jobs

There are n customers that need to be served. Customer i will only wait in queue for an exponentially distributed time with rate λ_i before departing the system. The service time of customer i has distribution F_i, and on completion of service of customer i a positive reward r_i is earned. There is a single server and the problem is to choose, after each service completion, which currently in queue customer to serve next so as to maximize the expected total return. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 659–663, 2015     

基于GSPN的舰载服务器系统可靠性建模及分析

提出一种基于广义随机Petri网(Generalized Stochastic Petri Net,GSPN)的舰载服务器系统可靠性分析方法。深入分析舰载服务器系统故障模式的基础上,建立冗余服务器子系统的GSPN模型和共享数据盘子系统的GSPN模型,进而综合得到舰载服务器系统的全局GSPN模型,有效模拟了舰载服务器系统的动态行为。仿真实验验证了所提方法的有效性,为舰载服务器系统的分析与设计提供理论参考。     

类“标枪”导弹两栖登陆反装甲作战弹道仿真分析

两栖登陆作战在战术上是最复杂、最危险的作战行动,登陆部队需要面对抗登陆方坚固的海岸防御背水抢滩作战,其危险性和困难可想而知。"工欲善其事,必先利其器",在兵器上的优势成为克服不利地理条件,形成火力优势的关键。类"标枪"反装甲导弹装备是两栖登陆作战中单兵反装甲作战的主要武器,仿真技术是类"标枪"反装甲导弹武器系统优化设计和性能研究的必要手段。介绍了单项仿真与综合仿真相结合的仿真方法,给出了类"标枪"反装甲导弹的弹道模型,利用Matlab编程语言进行了仿真验证,对改善导弹的弹道性能具有明显的实用价值。     

分布式海战场资源规划问题

分布式海战场资源规划是实现海上联合作战的关键。首先分析了海战场资源的分类及战场资源规划特点,建立了基于多智能体的分布式海战场资源规划系统,深入分析了该规划系统的组成和功能,并构造了相应的资源规划结构模型,为实现定性和定量相结合的海战场资源规划与管理提供了一条有效的途径。