Optimal inventory and dynamic admission policies for a retailer of seasonal products with affiliate programs and drop‐shipping

This article investigates the optimal inventory and admission policies for a “Clicks‐and‐Bricks” retailer of seasonal products that, in addition to selling through its own physical and online stores, also sells through third‐party websites by means of affiliate programs. Through postings on partners' webpages, an affiliate program allows a retailer to attract customers who would otherwise be missed. However, this retailer needs to pay a commission for each sale that originates from the website operators participating in the program. The retailer may also refer online orders to other sources (such as distributors and manufacturers) for fulfillment through a drop‐shipping agreement and thus earns commissions. This would be an option when, for example, the inventories at the physical stores were running low. Therefore, during the selling horizon, the retailer needs to dynamically control the opening/closing of affiliate programs and decide on the fulfillment option for online orders. On the basis of a discrete‐time dynamic programming model, the optimal admission policy of the retailer is investigated in this paper, and the structural properties of the revenue function are characterized. Numerical examples are given to show the revenue impact of optimal admission control. The optimal initial stocking decisions at the physical stores are also studied. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

基于集对分析的维修保障系统效能评估

在分析维修保障系统效能影响因素的情况下,应用集对分析方法建立了维修保障系统效能多指标评估模型,以定量的结果对维修保障系统效能进行综合评估,并与层次分析法和突变评价法的结果进行比较,结论一致.为维修保障系统效能评估问题寻求出一种新的方法,其评估结果可为决策提供定量依据.     

Reliability of a two-dimensional demand-based networked system with multistate components

Existing research on multistate system reliability has mainly focused on one-dimensional systems such as parallel systems, linear sliding window systems, and linearly consecutively connected systems. However, two-dimensional networked systems widely exist in real-world applications such as lighting systems, monitoring systems, and computer network systems. This research considers a two-dimensional networked system consisting of multistate components. The system fails if the cumulative performance of any row or any column cannot meet a predetermined demand. A novel reliability evaluation algorithm is proposed for the considered two-dimensional networked system by extending the universal generating function technique. Furthermore, the proposed model and reliability evaluation algorithm are extended to a two-dimensional networked system with phased missions. The proposed models and algorithms are illustrated by a matrix heating system in a thermoforming machine.     

基于神经网络的复杂导弹系统可靠性预测

介绍了如何利用神经网络对复杂导弹系统可靠性进行预测。对利用导弹地面测试数据和可靠性数据预测未来导弹可靠性问题进行了描述。给出了建模思路和方法框架。探讨了基于因子分析的可靠性数据特征选择方法、循环神经网络(RNN)、长短时记忆网络(LSTM)、门循环网络(GRU)以及输出数据融合方法。在实例中利用该方法对其飞行可靠性进行了预测,验证了方法的可行性与有效性。该方法可以充分利用复杂系统地面测试数据、可靠性数据中隐含的信息以及多种神经网络的优点,具有一定的通用性与实用性。     

高压大容量金属化膜脉冲电容器提高储能密度的工艺改进与试验研究

高能脉冲功率电源之储能器件即金属化膜脉冲电容器往往具有电压高、容量大的特点,而以现有的基膜材料和制造工艺,其相关产品的体积也普遍偏大,制约了新概念武器在更多中小型武器平台上的推广应用,因此开展提高脉冲电容器储能密度的理论分析和实验研究具有迫切的现实意义。为此,基于典型的双向拉伸聚丙烯薄膜(国产),通过改进金属电极、串联形式以及封装工艺,研究了提高其储能密度的优化方案,并在高压大电流循环浪涌条件下完成了试验验证。结果表明:在同等储能密度条件下,利用该优化方案生产的脉冲电容器较改进前寿命提高了41.7%;在同等寿命条件下,储能密度提高了13.8%,说明该优化方案具有可行性。     

基于VMD和SVM的舰船辐射噪声特征提取及分类识别

针对复杂海洋背景下舰船声频辐射噪声特征提取困难的问题,提出一种基于变分模态分解、中心频率、复杂度特征和支持向量机的舰船辐射噪声特征提取及分类识别方法。对四类舰船辐射噪声信号使用变分模态方法分解,得到一定数量的固有模态函数。通过比较提取能量最大的固有模态函数中心频率和排列熵作为特征参数,并利用支持向量机方法对四类舰船信号样本进行分类识别。实验结果表明,该方法可以实现对舰船辐射噪声的特征提取,与已有方法对比,该方法具有较高的识别率。     

高压大容量脉冲电容器保压过程中电压跌落的定量分析

针对金属化膜脉冲电容器在实际使用中由于充电结束以后较长的保压时间而产生电压跌落和能量损失,并最终导致脉冲功率电源系统的实际有效储能和储能密度下降这一实际问题,基于一种高压大容量脉冲电容器电压跌落的实验数据,分别从电导特性、自愈特性、极化特性及其与能量损失的相关性出发,推导了介质薄膜电导率与电压跌落的定量关系并进行了电导率测量实验,推导了自愈能量与电压跌落的定量关系并进行了寿命实验,阐述了松弛极化与电压跌落的定量关系并进行了仿真。结果表明,介质泄漏、自愈以及松弛极化在电压跌落中所占比例分别为29.64%、11.75%及58.35%,导致所研究电容器电压跌落的主要因素是松弛极化。     

红外多光谱图像弹道目标检测算法

在红外多光谱图像中,弹道导弹尾焰拥有两大特征,一是由强烈红外辐射引起的灰度差异,二是独特的光谱特性。然而,传统的单波段检测技术只利用了尾焰强烈的辐射特性,而近些年发展起来的多光谱检测技术则只利用了尾焰独特的光谱特性。为了充分利用导弹尾焰的两大特征,将单波段检测技术和多光谱检测技术结合起来,提出三种检测算法,并从算法的检测效果、运算量和鲁棒性三方面详细分析它们的优缺点。采用人工合成的红外多光谱图像进行验证,实验结果表明,相比单独使用单波段或多光谱的检测算法,融合算法的检测性能更好。     

应用地面电磁发射清除空间碎片方法

针对传统化学发射的空间碎片清除技术成本过高、难以实施的问题,提出应用地基电磁发射方式的空间碎片清除新方法。通过地面电磁发射的方式以低成本将射弹运送至空间,并通过释放空间微粒云团控制空间碎片离轨,进而实现对空间碎片的清除。由于取消使用占绝大部分成本的化学推进剂,所提出的应用地基电磁发射的空间碎片清除技术为空间碎片低成本清除提供了有效解决途径。     

基于机器视觉的洞库类目标自动识别技术

针对传统的洞库类目标识别方法所存在的不足,设计了一种基于可见光/红外线探测器和嵌入式DSP的洞库类目标主动探测和自动识别装置,根据洞库外观的结构特征建立了洞库识别的数学模型,提出了基于Hough变换的洞库类目标自动识别算法,并将洞库识别数学模型与Hough变换的处理流程有机结合起来,实现了不同外观结构的洞库类目标的正确识别。实验结果表明该洞库类目标识别算法具有较强的鲁棒性,可以有效地抑制噪声的影响,对由于预处理参数设置不合理所造成的洞库类目标边缘成为不连续曲线的现象也有良好的自适应性和自判断性。