VB程序设计课程教学的探索与实践

实践表明,对影响VB程序设计课程教学中存在的突出问题进行认真分析,充分利用网络教学平台,改革课堂教学方法、抓好上机实践环节。此举有效地激发了学生的学习兴趣,提高学生的编程能力,同时也有助于提高教学质量和效果。     

随机动态规划的混合算法研究

针对随机条件下动态规划模型的主要特点,运用智能算法混合编程理论,设计了一种探索多阶段决策问题的智能混合算法.该算法首先将问题转化成一族同类型的一步决策子问题,然后利用随机模拟和遗传算法,依据训练样本形成的训练神经元网络,在单步决策中寻求最优策略和最优目标值,逐个求解,再据初始状态逆序求出最优策略序列和最优目标值.仿真结果表明,该算法具有一定的通用性,初始设计点可以随机产生,其计算精度不因函数的非线性强弱而受影响,对目标和约束的限制较少,可应用于多种形式的随机多阶段决策优化问题,较好地满足了随机动态规划模型求解和优化的要求.     

LSP参数降维格型矢量量化应用研究

在分析LSP参数降维量化可行性的基础上,设计预处理机制实现了一种无码书LSP参数降维格型矢量量化算法,并提出了两个不同量化速率的VQ方案与MELP算法进行了对比。在24 bit/frame的实验方案中,组合4合成语音的PESQ均分超过了2.5,在无码书的条件下接近MELP有码书MSVQ的性能,可以满足低速率语音编码的音质要求并降低系统对空间复杂度和计算复杂度的需求。     

Competition under time‐varying demands and dynamic lot sizing costs

We develop a competitive pricing model which combines the complexity of time‐varying demand and cost functions and that of scale economies arising from dynamic lot sizing costs. Each firm can replenish inventory in each of the T periods into which the planning horizon is partitioned. Fixed as well as variable procurement costs are incurred for each procurement order, along with inventory carrying costs. Each firm adopts, at the beginning of the planning horizon, a (single) price to be employed throughout the horizon. On the basis of each period's system of demand equations, these prices determine a time series of demands for each firm, which needs to service them with an optimal corresponding dynamic lot sizing plan. We establish the existence of a price equilibrium and associated optimal dynamic lotsizing plans, under mild conditions. We also design efficient procedures to compute the equilibrium prices and dynamic lotsizing plans.© 2008 Wiley Periodicals, Inc. Naval Research Logistics 2009     

New product introduction against a predator: A bilevel mixed‐integer programming approach

We consider a scenario with two firms determining which products to develop and introduce to the market. In this problem, there exists a finite set of potential products and market segments. Each market segment has a preference list of products and will buy its most preferred product among those available. The firms play a Stackelberg game in which the leader firm first introduces a set of products, and the follower responds with its own set of products. The leader's goal is to maximize its profit subject to a product introduction budget, assuming that the follower will attempt to minimize the leader's profit using a budget of its own. We formulate this problem as a multistage integer program amenable to decomposition techniques. Using this formulation, we develop three variations of an exact mathematical programming method for solving the multistage problem, along with a family of heuristic procedures for estimating the follower solution. The efficacy of our approaches is demonstrated on randomly generated test instances. This article contributes to the operations research literature a multistage algorithm that directly addresses difficulties posed by degeneracy, and contributes to the product variety literature an exact optimization algorithm for a novel competitive product introduction problem. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

Two‐machine flow shop scheduling with common due window to minimize weighted number of early and tardy jobs

This article studies two due window scheduling problems to minimize the weighted number of early and tardy jobs in a two‐machine flow shop, where the window size is externally determined. These new scheduling models have many practical applications in real life. However, results on these problems have rarely appeared in the literature because of a lack of structural and optimality properties for solving them. In this article, we derive several dominance properties and theorems, including elimination rules and sequencing rules based on Johnsos order, lower bounds on the penalty, and upper bounds on the window location, which help to significantly trim the search space for the problems. We further show that the problems are NP‐hard in the ordinary sense only. We finally develop efficient pseudopolynomial dynamic programming algorithms for solving the problems. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009     

What you should know about approximate dynamic programming

Approximate dynamic programming (ADP) is a broad umbrella for a modeling and algorithmic strategy for solving problems that are sometimes large and complex, and are usually (but not always) stochastic. It is most often presented as a method for overcoming the classic curse of dimensionality that is well‐known to plague the use of Bellman's equation. For many problems, there are actually up to three curses of dimensionality. But the richer message of approximate dynamic programming is learning what to learn, and how to learn it, to make better decisions over time. This article provides a brief review of approximate dynamic programming, without intending to be a complete tutorial. Instead, our goal is to provide a broader perspective of ADP and how it should be approached from the perspective of different problem classes. © 2009 Wiley Periodicals, Inc. Naval Research Logistics 2009     

一种适用于点和区间混合型维度数据集的多维索引

点和区间混合型维度数据集是空间数据库系统和GIS中重要的数据对象.在分析SS树的基础上,提出了一种适用于索引点和区间混合型维度数据集的索引结构--PI树.PI树利用超球划分数据集的多维空间,以提高结点存储利用率,从而降低数据插入时的I/O次数.文章给出了PI树插入、删除和查询算法的形式化描述.理论分析和实验结果表明,所提的PI树性能上总体优于R·树.     

无人机运动模糊图像复原技术

在无人机飞行过程中,由于成像系统会受到相对运动、姿态变化、机械振动、镜头离焦以及大气湍流效应等影响,造成获取的图像产生退化.由于图像复原问题通常情况下是病态的,综合利用了无人机运动的先验信息,提出了不同运动模糊情况下点扩散函数的估计方法,采用维纳滤波复原算法估计图像,给出了适用于无人机成像制导系统的图像复原方案.最后经仿真实验证明,该算法图像复原效果好,计算量小,抗噪声鲁棒性强,有较大的工程应用价值.     

新阶段深化武警部队后勤保障社会化的思考

随着我国社会经济的快速发展,武警部队后勤保障社会化改革工作也进入新的阶段,应从着力点的选择、具体措施的制定和强化监督管理三个方面,对新阶段武警部队后勤保障方式社会化工作进行改革。