Explicit solution of relative entropy weighted control

We consider the minimization over probability measures of the expected value of a random variable, regularized by relative entropy with respect to a given probability distribution. In the general setting we provide a complete characterization of the situations in which a finite optimal value exists and the situations in which a minimizing probability distribution exists. Specializing to the case where the underlying probability distribution is Wiener measure, we characterize finite relative entropy changes of measure in terms of square integrability of the corresponding change of drift. For the optimal change of measure for the relative entropy weighted optimization, an expression involving the Malliavin derivative of the cost random variable is derived. The theory is illustrated by its application to several examples, including the case where the cost variable is the maximum of a standard Brownian motion over a finite time horizon. For this example we obtain an exact optimal drift, as well as an approximation of the optimal drift through a Monte-Carlo algorithm.     

ZW多产品间歇过程调度及在线调整

针对多产品间歇过程调度提出了分层递阶的Petri网建模方法，利用赋时Petri和Petri网的简化技术描述不同层次的生产问题，具有很强的模型描述能力。另外，在调度决策层可以方便地集成优化策略和在线调整算法，使问题求解更加灵活。     

Optimal temperature policies for catalytic transport reactors under periodic operation

The influence of inlet gas concentration cycling on the optimal temperature policy of catalytic transport reactors is studied theoretically. The model considered is based on plug flow of gas and catalyst particles with negligible interand intra-particle diffusional resistances and concentration dependent deactivation kinetics. To utilise the concentration of the reactant and the activity of the deactivating catalyst fully a proper temperature sequence along the reactor is needed. Thus, a general optimal temperature policy using the continuous minimum principle is derived for the reactor under periodic operation. The model equations are solved analytically for gas concentration, activity and temperature profiles. Resonance behaviour (maximum in conversion with pulse width) is obtained using the optimal temperature policy for certain sets of parameters. The effects of activation energy groups, reaction and deactivation constant groups and inlet temperature on the optimal temperature policy under periodic operation are evaluated. In all cases an improvement in conversion with the optimal temperature policy under periodic operation over that with an isothermal policy under periodic operation is obtained. A suboptimal policy, comprising constant temperature over different reactor sections, which is useful for implementation purposes is also discussed.     

大规模水电系统优化调度降维方法研究I:理论分析

中国水电系统规模持续扩张,使得已有方法在求解大规模水电调度问题时,存在严重维数灾及早熟收敛等不同程度局限,亟需分析已有方法以便发现其瓶颈所在,为探寻能均衡求解效率与计算精度的实用化方法提供有益参考。为此,首先深入研究了线性规划、二次规划和动态规划等多种方法的计算复杂度,然后定量对比分析了各方法在不同情景下的适用性,最后提出“四维一体可拓降维”总体思想,并给出具体的降维方法与策略,建议从空间维、时间维、状态维和组合维等4个方面开展综合研究,以切实服务于大规模水电系统优化调度的高效优质求解。     

太阳能供热系统优化设计的相关问题研究

随着我国建筑总量和建筑能耗的快速增长,传统的供热方式已难以满足建筑供热的需求,而利用太阳能为建筑物供热,则可获得良好的节能和环保效益。就太阳能供热系统优化设计的相关问题进行了分析和研究,以期能为太阳能供热技术的推广和应用提供一定的理论依据。     

THE ESTIMATION AND PREDICTION OF SUBSET BILINEAR TIME SERIES MODELS WITH APPLICATIONS

Abstract. In this paper we define subset bilinear time series models, and then describe an algorithm for the estimation of these models. It is also pointed out that for this class of non-linear time series models, it is possible to obtain optimal several step predictors. The estimation technique of these models is illustrated with respect to three time series, and the optimal several steps ahead forecasts of these time series models are calculated. A comparison of these forecasts is made with the forecasts obtained by the best linear autoregressive and threshold autoregressive models. The residuals obtained from the models are tested for independence and Gaussianity using higher order moments.     

WSN中基于线性规划的多类别目标覆盖算法

多类别目标覆盖问题是目前无线传感器网络中的研究热点。针对现有目标覆盖算法在时间效率、网络生命周期等方面的不足,将多类别目标覆盖问题建模为基于线性规划的网络生命周期最大化问题,提出一种基于分簇的目标覆盖算法。该算法依据节点的剩余能量和感应能力,在每个簇结构内求解最优覆盖集的基础上得到接近于最优解的全局覆盖集,进而调度节点相应的感应模块去覆盖其感知范围内同属性的目标。实验结果表明,该算法是有效的,在网络生命周期和时间效率等方面均优于CWGC方案,接近于线性规划最优值。     

自适应收扩系数的双中心协作QPSO算法

针对量子粒子群优化(QPSO)算法迭代后期种群多样性下降、收敛速度慢、易陷入局部最优的缺点,提出一种自适应收缩-扩张系数的双中心协作最子粒子群优化算法。该算法从2个方面进行改进:(1)自适应调节收缩-扩张系数,其目的是帮助粒子跳出局部最优点,提高粒子的全局搜索能力;(2)双重更新全局最优位置,即在每次迭代中,先后分别采用2种不同的方式更新全局最优位置。第1种方式与QPSO算法一致,第2种方式则引入双中心粒子,使其和当前全局最优位置在相应维度上合作,从而达到更新全局最优位置的目的。从固定迭代次数和固定精度角度分析算法性能,仿真结果表明,相比于QPSO算法,该算法在保证复杂度较低的情况下,可提高收敛速度,增强全局和局部搜索能力。     

均衡模糊C均值聚类算法

模糊C均值聚类算法没有考虑各类样本容量因素,当各类样本容量差异较大时,其聚类判决将向小样本类倾斜。提出一种新的聚类算法——均衡模糊C均值聚类,对模糊C均值聚类算法最小化目标函数进行修正,使得改进的目标函数包含了样本容量因素,利用粒子群算法并以样本模糊隶属度为编码对象求解参数优解。从理论上分析了该算法的性质,通过仿真实验验证了所提算法对平衡、不平衡数据集的有效性。     

动态传感器网络区域受限的移动sink路径选择研究

针对sink区域受限及节点特征参数的问题,如何规划sink路径选择以满足动态传感器网络高效数据收集及低能耗的要求,提出了一种动态传感器网络区域受限的移动sink路径选择方法。该方法在缓存节点辅助通信模式下,建立sink受限区域图模型。针对不同应用情况,分别讨论了sink移动全局路径信息已知和sink移动局部路径信息已知这两种情况下的最优移动路径。在全局路径信息已知时,采用Vornon单元划分的思想求解总传输能耗和节点平均负载;在局部路径信息已知时,采用启发式策略进行路径寻优,并证明其路径寻优的正确性。最后通过仿真实验与理论计算来验证移动sink最佳路径寻优策略的有效性和可行性。