弹性轨道磁悬浮控制系统模型降阶研究

在磁悬浮控制系统中,常常忽略轨道的弹性来设计控制算法。在这种控制算法作用下,当轨道刚度较小时,系统容易产生振动。为解决该问题,可以将轨道弹性加入悬浮模型,然后设计控制算法。考虑轨道弹性之后,悬浮系统的模型会比较复杂,控制算法难以在工程实现。为此,采用Hankel范数近似法对考虑轨道弹性后的模型进行降阶,并且在降阶模型的基础上设计控制算法,解决了轨道弹性引发的系统振动问题。并且,这种方法容易在工程中实现。文章最后利用仿真结果验证了降阶方法的可行性。     

Schedule design for liner services under vessel speed reduction incentive programs

Gas and particulate emissions from ship transportation have been increasing in recent years. In order to mitigate ship emissions near coastal areas, voluntary vessel speed reduction incentive programs (VSRIPs) were put in place by a number of ports. This paper studies a schedule design problem faced by liner shipping companies under VSRIPs. It proposes a mixed-integer nonlinear mathematical model for the minimization of the total cost, consisting of fuel cost, as well as operating cost, minus dockage refunds. The model balances three determinants, that is, the compliance of VSRIPs, the speed limit (the maximum physical speed of ships and the upper speed limit imposed by VSRIPs), and the limited number of ships. An enumerative algorithm and a piecewise-linear approximation algorithm are developed, based on some properties of the nonlinear model. The efficiency of the proposed algorithms is validated through extensive computational experiments.     

Optimal policies for stochastic clearing systems with time-dependent delay penalties

We study stochastic clearing systems with a discrete-time Markovian input process, and an output mechanism that intermittently and instantaneously clears the system partially or completely. The decision to clear the system depends on both quantities and delays of outstanding inputs. Clearing the system incurs a fixed cost, and outstanding inputs are charged a delay penalty, which is a general increasing function of the quantities and delays of individual inputs. By recording the quantities and delays of outstanding inputs in a sequence, we model the clearing system as a tree-structured Markov decision process over both a finite and infinite horizon. We show that the optimal clearing policies, under realistic conditions, are of the on-off type or the threshold type. Based on the characterization of the optimal policies, we develop efficient algorithms to compute parameters of the optimal policies for such complex clearing systems for the first time. We conduct a numerical analysis on the impact of the nonlinear delay penalty cost function, the comparison of the optimal policy and the classical hybrid policy (ie, quantity and age thresholds), and the impact of the state of the input process. Our experiments demonstrate that (a) the classical linear approximation of the cost function can lead to significant performance differences; (b) the classical hybrid policy may perform poorly (as compared to the optimal policies); and (c) the consideration of the state of the input process makes significant improvement in system performance.     

基于随机搜索策略的中继卫星调度方法

高质量的调度方案不仅能满足用户的需求,还能为中继卫星系统的计划编制提供科学的决策手段和依据。针对日益多样化的用户需求,采用全新的中继卫星调度应用模式,允许用户提交多个可以滑动的时间窗口。面向这种调度模式,考虑中继业务中任务调度的灵活性和任务间的冲突,构建考虑多滑动窗口的中继卫星调度模型,并设计基于随机搜索策略的中继卫星调度算法。算法包括任务资源匹配与邻域生成、可用时间段生成、任务冲突分析、邻域搜索与冲突消解以及资源与任务集更新5个算子。通过仿真实验将该算法与基于时间自由度的启发式算法进行对比,验证了算法的有效性。     

粘弹性谱随机有限元

发展了一种粘弹性谱随机有限元法(VSSFEM),并将其用于固体火箭发动机装药结构随机分析。基于不可压或近似不可压粘弹性增量有限元方法和正交展开理论,考虑固体推进剂泊松比的随机性,推导了粘弹性谱随机有限元列式,最后对弹性约束的圆柱形中孔药柱进行了随机分析。算例分析表明该方法能够正确有效地进行粘弹性体随机分析。     

卡尔曼滤波框架下优化增益异类噪声处理方法及其应用

针对基于卡尔曼滤波框架算法只能处理已知高斯噪声系统的局限性,设计能够同时处理含有异类噪声系统的改进算法.将不确定系统受到的干扰分成高斯噪声和未知有界噪声,对噪声特点进行分析,并将其加入状态方程和观测方程;在吸收集员滤波优点的基础上,对标准卡尔曼滤波进行改进,通过计算包含两种异类噪声系统状态的最小均方误差,得到该条件下滤...     

Simultaneous production of market‐specific and global products: A two‐stage stochastic program with additional demand after recourse

This paper analyzes the simultaneous production of market‐specific products tailored to the needs of individual regions and a global product that could be sold in many regions. We assume that the global product costs more to manufacture, but allows the decision concerning the allocation of products to regions to be delayed until after the manufacturing process has been completed. We further assume that there is additional demand after the region allocation but prior to delivery, extending the two‐stage stochastic program with recourse to include additional stochastic demand after the recourse. This scenario arises, for example, when there is additional uncertainty during a delivery delay which might occur with transoceanic shipments. We develop conditions for optimality assuming a single build‐allocate‐deliver cycle and stochastic demand during both the build and deliver periods. The optimal policy calls for the simultaneous production of market‐specific and global products, even when the global product is substantially more costly than the market‐specific product. In addition, we develop bounds on the performance of the optimal policy for the multicycle problem. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 438–461, 2003     

Optimal stopping in software testing

In this paper we address the problem of how to decide when to terminate the testing/modification process and to release the software during the development phase. We present a Bayesian decision theoretic approach by formulating the optimal release problem as a sequential decision problem. By using a non‐Gaussian Kalman filter type model, proposed by Chen and Singpurwalla (1994), to track software reliability, we are able to obtain tractable expressions for inference and determine a one‐stage look ahead stopping rule under reasonable conditions and a class of loss functions. © 2002 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

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.     

To wait or not to wait: Optimal ordering under lead time uncertainty and forecast updating

There has been a dramatic increase over the past decade in the number of firms that source finished product from overseas. Although this has reduced procurement costs, it has increased supply risk; procurement lead times are longer and are often unreliable. In deciding when and how much to order, firms must consider the lead time risk and the demand risk, i.e., the accuracy of their demand forecast. To improve the accuracy of its demand forecast, a firm may update its forecast as the selling season approaches. In this article we consider both forecast updating and lead time uncertainty. We characterize the firm's optimal procurement policy, and we prove that, with multiplicative forecast revisions, the firm's optimal procurement time is independent of the demand forecast evolution but that the optimal procurement quantity is not. This leads to a number of important managerial insights into the firm's planning process. We show that the firm becomes less sensitive to lead time variability as the forecast updating process becomes more efficient. Interestingly, a forecast‐updating firm might procure earlier than a firm with no forecast updating. © 2009 Wiley Periodicals, Inc. Naval Research Logistics, 2009