推进党内民主建设 增强党的团结统一

胡锦涛同志在党的十七大报告中,将"发展党内民主"提升到了"党内民主建设"的战略高度,并对推进党内民主建设明确了目标任务和有效方略。深入学习领会、准确把握讲话的这一精神,对于开创党内民主建设新局面具有重大而深远的意义。     

Clustered coverage orienteering problem of unmanned surface vehicles for water sampling

This study investigates a clustered coverage orienteering problem (CCOP), which is a generalization of the classical orienteering problem. The problem is widely motivated by the emerging unmanned techniques (eg, unmanned surface vehicles and drones) applied to environmental monitoring. Specifically, the unmanned surface vehicles (USVs) are used to monitor reservoir water quality by collecting samples. In the CCOP, the water sampling sites (ie, the nodes) are grouped into clusters, and a minimum number of nodes must be visited in each cluster. With each node representing a certain coverage area of the water, the objective of the CCOP is to monitor as much as possible the total coverage area in one tour of the USV, considering that overlapping areas provide no additional information. An integer programming model is first formulated through a linearization procedure that captures the overlapping feature. A two-stage exact algorithm is proposed to obtain an optimal solution to the problem. The efficiency and effectiveness of the two-stage exact algorithm are demonstrated through experiments on randomly generated instances. The algorithm can effectively solve instances with up to 60 sampling sites.     

Optimal production ramp-up in the smartphone manufacturing industry

Motivated by challenges in the smartphone manufacturing industry, we develop a dynamic production ramp-up model that can be applied to economically satisfy nonstationary demand for short-life-cycle products by high-tech companies. Due to shorter life cycles and more rapid evolution of smartphones, production ramp-up has been increasingly critical to the success of a new smartphone. In the production ramp-up, the key challenge is to match the increasing capacity to nonstationary demand. The high-tech smartphone manufacturers are urged to jointly consider the effect of increasing capacity and decreasing demand. We study the production planning problem using a high-dimensional Markov decision process (MDP) model to characterize the production ramp-up. To address the curse of dimensionality, we refine Monte Carlo tree search (MCTS) algorithm and theoretically analyze its convergence and computational complexity. In a real case study, we find that the MDP model achieves revenue improvement by stopping producing the existing product earlier than the benchmark policy. In synthetic instances, we validate that the proposed MCTS algorithm saves computation time without loss of solution quality compared with traditional value iteration algorithm. As part of the Lenovo production solution, our MDP model enables high-tech smartphone manufacturers to better plan the production ramp-up.     

Revenue maximization in two-station tandem queueing systems

We study optimal pricing for tandem queueing systems with finite buffers. The service provider dynamically quotes prices to incoming price sensitive customers to maximize the long-run average revenue. We present a Markov decision process model for the optimization problem. For systems with two stations, general-sized buffers, and two or more prices, we describe the structure of the optimal dynamic pricing policy and develop tailored policy iteration algorithms to find an optimal pricing policy. For systems with two stations but no intermediate buffer, we characterize conditions under which quoting either a high or a low price to all customers is optimal and provide an easy-to-implement algorithm to solve the problem. Numerical experiments are conducted to compare the developed algorithms with the regular policy iteration algorithm. The work also discusses possible extensions of the obtained results to both three-station systems and two-station systems with price and congestion sensitive customers using numerical analysis.     

基于杂草算法的超磁致伸缩作动器耦合模型识别

考虑磁滞损耗、动态应力等因素的超磁致伸缩作动器磁滞模型可有效揭示电-磁-机-热多场耦合效应,但准确识别其非线性模型往往存在较大困难。智能杂草算法具有激烈的竞争机制和较强的搜索能力,可用于解决作动器多目标物理参数辨识问题。传统算法的种子数量以线性方式产生且分布方差与适应度缺乏联系,极大地影响了算法收敛速度和模型识别精度。为此,提出一种非线性繁殖和分布的混合改进杂草算法,并将其应用于超磁致伸缩作动器模型识别。实验表明:改进算法具有较强的噪声抑制能力,能精确辨识含有噪声扰动的作动器磁滞非线性模型物理参数;模型预测值和实验数据误差较小,所识别参数可使磁滞非线性模型较为全面地描述作动器多场耦合机理和动态特性。     

疲劳裂纹闭合的非线性超声在线测量

建立了外部载荷作用下用非线性振动-声场调制指数表征裂纹尺寸的数学模型。根据对外载荷与塑性致闭应力共同作用下裂纹面的开闭响应的分析,提出了裂纹张开和闭合应力的在线测量方法。在一块含中心穿透裂纹的铝合金薄板试件上进行了裂纹闭合参数的测量实验,实验结果表明,使用振动-声场调制技术在线测量裂纹闭合参数是可行且有效的,且该方法还能用于分析小裂纹的特殊开闭行为。     

战役野战油库油料输送力量优化分配研究

如何科学、合理分配战役野战油库油料输送力量是战时油料保障必须面临的一个实际问题。首先根据战役野战油库运油车分配模型得到一个运油车初始分配方案,然后运用计算机模拟技术对分配方案进行模拟,并根据模拟结果不断调整,直至得到优化的分配方案,为制定战役野战油库油料输送计划提供决策依据。     

基于AOS包业务模型的最优帧长与吞吐量性能

分析了影响AOS包业务吞吐量性能的因素及帧长度对系统吞吐量性能的影响,建立了包复用效率及差错信道下吞吐量的数学模型,通过仿真验证数学模型的可靠性。并进一步得出差错信道下使系统吞吐量性能最大的最优帧长度配置。研究结果为以吞吐量性能为指标,通过信道状态自适应调节帧长来优化AOS协议提供了理论依据。     

基于双向映射的非网格型全向图展开插值方法

原始的全向图存在严重的同心圆环状变形,通常需展开为更适合人眼观察的柱面全景图像。结合折反射全向成像特点,提出一种基于双向映射的全向图展开为柱面全景图像的插值方法,通过光路跟踪得到图像间的坐标映射关系,将所要生成的柱面全景图中每一点正向映射到原始的全向图中,确定插值邻域点;将这些邻域点逆向投影到柱面全景图中,针对邻域点在柱面全景图中呈非网格型分布的特点,采用非均匀二维插值算法进行图像插值运算。该方法既准确地定位插值邻域点,又避免了全向图的非线性畸变对邻域点权重计算的不利影响。实验证明该方法能有效提高插值精度和展开后图像的质量。     

Potential impact of recharging plug‐in hybrid electric vehicles on locational marginal prices

Plug‐in hybrid electric vehicles (PHEVs), upon market penetration, will create additional recharging loads to the electric power systems. This article considers different recharging scenarios and uses game theoretic models to study the potential impact of the recharging loads on locational marginal prices (wholesale electricity prices). Computational results from a Pennsylvania‐New Jersey‐Maryland Interconnection case study show that, under the existing recharging infrastructures, even a small magnitude of load increase caused by PHEV recharging could have a significant undesirable impact on locational marginal prices. The impact could be mitigated to a varying extent by the availability of possible future recharging infrastructures, including realtime pricing recharging meters, battery stations, or vehicle‐to‐grid technology.© 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010