融合空间偏好和语义的个体活动识别方法

个体活动识别对用户画像、个性化推荐、异常行为检测、群体行为分析和基于活动的资源配置优化具有重要价值。提出了一种基于稀疏的社交媒体签到数据的个体活动语义识别方法,从签到数据中提取活动行为的时间周期性和趋势性特征,并采用空间偏好量化算法,从个体与群体活动的空间关联中提取群体和个体的空间访问偏好,使用自然语言嵌入工具BERT模型提取访问兴趣点的语义。时间特征、空间偏好特征和访问兴趣点名称语义特征共同构成表征群体、个体偏好的时空联合特征,通过极限梯度提升分类器对其进行分类,得到活动语义识别结果。在Foursquare数据集上的对比实验和消融实验中验证了所提活动语义识别模型可以有效提升活动语义识别的准确性。     

基于粒子群优化的观测站部署算法

针对红外观测站部署问题,在研究观测站位置对定位精度影响的基础上,提出了基于粒子群优化的观测站部署算法。首先对ECEF坐标系下的CRLB矩阵进行推导;然后将观测站优化部署问题抽象为非线性规划模型,并将红外传感器联合定位的CRLB作为目标函数;最后采用粒子群优化算法求解该模型,避免了传统的非线性规划算法需要求解目标函数梯度的难题。结果表明,本文的部署算法具有一定的理论依据和工程意义;可以为实际红外观测站的静态部署和动态部署提供参考。     

The burglar problem with multiple options

We consider the burglar problem in which a burglar can either retire or choose among different types of burglaries, with each type having its own success probability and reward distribution. Some general structural results are established and, in the case of exponentially distributed reward distributions, a solution technique is presented. The burglar problem's relationship to a stochastic knapsack problem with a random exponentially distributed knapsack capacity is shown. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 359–364, 2014     

A branch‐and‐price approach for the stochastic generalized assignment problem

In this article, we address a stochastic generalized assignment machine scheduling problem in which the processing times of jobs are assumed to be random variables. We develop a branch‐and‐price (B&P) approach for solving this problem wherein the pricing problem is separable with respect to each machine, and has the structure of a multidimensional knapsack problem. In addition, we explore two other extensions of this method—one that utilizes a dual‐stabilization technique and another that incorporates an advanced‐start procedure to obtain an initial feasible solution. We compare the performance of these methods with that of the branch‐and‐cut (B&C) method within CPLEX. Our results show that all B&P‐based approaches perform better than the B&C method, with the best performance obtained for the B&P procedure that includes both the extensions aforementioned. We also utilize a Monte Carlo method within the B&P scheme, which affords the use of a small subset of scenarios at a time to estimate the “true” optimal objective function value. Our experimental investigation reveals that this approach readily yields solutions lying within 5% of optimality, while providing more than a 10‐fold savings in CPU times in comparison with the best of the other proposed B&P procedures. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 131–143, 2014     

微槽结构单点金刚石飞切加工的切削力建模

超精密单点金刚石飞刀切削技术是一种比较新颖的微槽类结构加工方式。在飞切过程中,切削力是切削过程中重要的物理量,对加工后的表面质量、刀具磨损等有着直接影响。提出了一种基于直角微切削理论的动态微槽类结构飞切的力学模型,基于微切削理论,得到了前、后刀面切削力的理论模型。根据飞切的几何运动特征,建立了飞切过程中剪切角的计算模型,并根据单圈飞切实验得到了飞切过程中剪切面的变化规律。为了验证模型的正确性,采用不同切削参数进行了多圈重叠飞切实验,对切削力进行了测量和分析。实验得到的切削力大小和变化规律与理论模型计算得到的基本一致,证明了该切削力模型的有效性。     

基于可能性决策的敌对危机行动预测与仿真

可能性决策能较好地应对军事领域常常出现的概率难以获得,或者强调“出奇制胜”而有意规避概率风险的情形,是解决知识不完备情况下敌对行动预测的有力手段。从可能性理论基本公理体系出发,结合动态规划方法,提出并证明可能性决策的最优化定理,给出多步条件下可能性决策的实现算法,结合危机条件下敌对行动预测的范例和仿真分析,与传统概率风险决策进行比较,体现可能性决策的优越性,为该方法的推广应用创造条件。     

A three‐stage procurement optimization problem under uncertainty

This article examines a problem faced by a firm procuring a material input or good from a set of suppliers. The cost to procure the material from any given supplier is concave in the amount ordered from the supplier, up to a supplier‐specific capacity limit. This NP‐hard problem is further complicated by the observation that capacities are often uncertain in practice, due for instance to production shortages at the suppliers, or competition from other firms. We accommodate this uncertainty in a worst‐case (robust) fashion by modeling an adversarial entity (which we call the “follower”) with a limited procurement budget. The follower reduces supplier capacity to maximize the minimum cost required for our firm to procure its required goods. To guard against uncertainty, the firm can “protect” any supplier at a cost (e.g., by signing a contract with the supplier that guarantees supply availability, or investing in machine upgrades that guarantee the supplier's ability to produce goods at a desired level), ensuring that the anticipated capacity of that supplier will indeed be available. The problem we consider is thus a three‐stage game in which the firm first chooses which suppliers' capacities to protect, the follower acts next to reduce capacity from unprotected suppliers, and the firm then satisfies its demand using the remaining capacity. We formulate a three‐stage mixed‐integer program that is well‐suited to decomposition techniques and develop an effective cutting‐plane algorithm for its solution. The corresponding algorithmic approach solves a sequence of scaled and relaxed problem instances, which enables solving problems having much larger data values when compared to standard techniques. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

Asymptotic analysis of periodic policies for the inventory routing problem

In this article, a distribution system is studied where the sum of transportation and inventory costs is to be minimized. The inventory holding cost is assumed to be the same for all retailers. A fixed partition (FP) periodic policy is proposed with tight asymptotic worst‐case performance of 3/2 with respect to the best possible policy. This bound cannot be improved in the class of FP periodic policies. In partition‐based PB policies, the retailers are first partitioned into sets and then the sets are grouped in such a way that sets of retailers within a group are served together at selected times. A PB periodic, policy is presented with tight worst‐case asymptotic performance of with respect to the best possible policy. This latter performance improves the worst‐case asymptotic performance of of the previously best known policy for this problem. We also show that the proposed PB periodic policy has the best worst‐case asymptotic performance within the class of PB policies. Finally, practical heuristics inspired by the analyzed policies are designed and tested. The asymptotic worst–case performances of the heuristics are shown to be the same of those of the analyzed policies. Computational results show that the heuristics suggested are less than 6.4% on average from a lower bound on the optimal cost when 50 or more retailers are involved. © 2013 Wiley Periodicals, Inc. Naval Research Logistics 00: 000–000, 2013     

装备保障抽组力量物资装载模型

对装备保障抽组力量的物资装载问题进行了数学描述,建立了以实现全部物资尽量分散装载为目标,以同类物资集中装载、车辆承载物资总体积不超过车辆有效容积、车辆承载物资总重量不超过车辆标记载重量、物资必须装载且不被重复装载等为主要约束的数学模型,并进行了求解.最后通过实例解算验证了模型的有效性.     

基于相位估计的湍流降质图像盲复原

地基望远镜观测的空间目标图像受大气湍流的影响,其分辨率受到很大的限制。为了提高湍流降质图像的复原效果,提出一种改进的盲解卷积方法。首先,考虑观测图像受到高斯噪声和泊松噪声的干扰,推导出基于混合噪声模型的盲解卷积代价函数;然后,根据傅里叶光学原理,利用波前相位表示点扩展函数,将点扩展函数从像素值估计转换为参数估计;最后,通过参数化表示方式,将代价函数寻优从约束最优化问题转换为无约束最优化问题。模拟实验结果验证了本文模型与数值算法的有效性。