Preconditioned finite element algorithms for 3D Stokes flows

Preconditioned conjugate gradient algorithms for solving 3D Stokes problems by stable piecewise discontinuous pressure finite elements are presented. The emphasis is on the preconditioning schemes and their numerical implementation for use with Hermitian based discontinuous pressure elements. For the piecewise constant discontinuous pressure elements, a variant implementation of the preconditioner proposed by Cahouet and Chabard for the continuous pressure elements is employed. For the piecewise linear discontinuous pressure elements, a new preconditioner is presented. Numerical examples are presented for the cubic lid-driven cavity problem with two representative elements, i.e. the Q2-PO and the Q2-P1 brick elements. Numerical results show that the preconditioning schemes are very effective in reducing the number of pressure iterations at very reasonable costs. It is also shown that they are insensitive to the mesh Reynolds number except for nearly steady flows (Re_m → 0) and are almost independent of mesh sizes. It is demonstrated that the schemes perform reasonably well on non-uniform meshes.     

Difference Discrete Variational Principle in Discrete Mechanics and Symplectic Algorithm

We propose the difference discrete variational principle in discrete mechanics and symplectic algorithmwith variable step-length of time in finite duration based upon a noncommutative differential calculus established inthis paper. This approach keeps both symplecticity and energy conservation discretely. We show that there exists thediscrete version of the Euler-Lagrange cohomology in these discrete systems. We also discuss the solution existencein finite time-length and its site density in continuous limit, and apply our approach to the pendulum with periodicperturbation. The numerical results are satisfactory.     

一类多步并行Runge—Kutta公式

本文构造了一类适合在多处理机系统上实现的并行Ｒｕｎｇｅ－Ｋｕｔｔａ公式，对于其中的具体公式证明了收敛性，给出它的稳定区域，数值例子表明，该公式可以有效地求解常微分方程初值问题。     

光互连中二元计算全息算法的研究

二元计算全息(BCGH)是光学信息处理中一个重要元件,其在动态光互连中被广泛使用.为了更好地在光互连中应用BCGH,本文设计改进了二元计算全息的选代算法,比较了几种内能函数下的迭代算法所设计的BCGH,对其象质的不同指标进行了分析.结果表明,用迭代搜索算法是光互连应用中设计BCGH的一种较理想算法.     

非光滑多目标规划的不动点算法(英)

本文讨论不动点算法在非光滑多目标规划中的应用，得到了一些新的最优性条件以及不动点与非光滑多目标的解之间的关系，并且给出了解非光滑多目标规划的不动点算法的收敛性．     

A Quasi-Newton Penalty Barrier Method for Convex Minimization Problems

We describe an infeasible interior point algorithm for convex minimization problems. The method uses quasi-Newton techniques for approximating the second derivatives and providing superlinear convergence. We propose a new feasibility control of the iterates by introducing shift variables and by penalizing them in the barrier problem. We prove global convergence under standard conditions on the problem data, without any assumption on the behavior of the algorithm.     

时域有限差分法在光波导分析中的应用及改进

对时域有限差分算法在圆柱坐标下弱导光纤中应用时吸收边界条件的设置及其对计算精度的影响进行了讨论，提出了改善的方法。并且将这种方法应用于一般光纤和光电子晶体光纤传输特性的计算，得到了有用结果。     

Feature selection algorithm in classification learning using support vector machines

An algorithm for selecting features in the classification learning problem is considered. The algorithm is based on a modification of the standard criterion used in the support vector machine method. The new criterion adds to the standard criterion a penalty function that depends on the selected features. The solution of the problem is reduced to finding the minimax of a convex-concave function. As a result, the initial set of features is decomposed into three classes—unconditionally selected, weighted selected, and eliminated features. Original Russian Text Yu.V. Goncharov, I.B. Muchnik, L.V. Shvartser @, 2008, published in Zhurnal Vychislitel’noi Matematiki i Matematicheskoi Fiziki, 2008, Vol. 48, No. 7, pp. 1318–1336.     

非线性极大极小系统全局优化算法的分析

非线性极大极小系统的全局优化可用于柔性制造和智能交通的决策与控制.实现了非线性极大极小系统的全局优化算法的仿真,并进行了计算时间分析.数值实验表明了全局优化算法的可行性.算法的计算时间主要由系统的优化极大射影矩阵数目决定,而优化极大射影矩阵数目与系统解析式中单极大式的系数紧密相关,系数取值越分散,简约极大射影矩阵的效果越好,计算效率越高.     

多阶段M-SV投资组合优化的离散近似迭代法研究

文章提出了离散近似迭代法,用该方法求解具有交易成本和交易量限制的多阶段均值一半方差(M-sV)投资组合模型.离散近似迭代方法的基本思路为:首先,将连续型状态变量离散化,根据网络图的构造方法将上述模型转化多阶段赋权有向图;其次,运用嘉量原理求出起点至终点的最长路程,即获得模型的一个可行解;最后,以该可行解为基础,继续迭代直到前后两个可行解非常接近.文章还证明了该方法的收敛性和复杂性.