A new pivoting algorithm for the linear complementarity problem allowing for an arbitrary starting point

The linear complementarity problem is to find nonnegative vectors which are affinely related and complementary. In this paper we propose a new complementary pivoting algorithm for solving the linear complementarity problem as a more efficient alternative to the algorithms proposed by Lemke and by Talman and Van der Heyden. The algorithm can start at an arbitrary nonnegative vector and converges under the same conditions as Lemke's algorithm.This research is part of the VF-program Competition and Cooperation.     

On a new stochastic global optimization algorithm based on censored observations

In this paper a new algorithm is proposed for global optimization problems. The main idea is that of modifying a standard clustering approach by sequentially sampling the objective function while adaptively deciding an appropriate sample size. Theoretical as well as computational results are presented.     

A technique for speeding up the solution of the Lagrangean dual

We propose techniques for the solution of the LP relaxation and the Lagrangean dual in combinatorial optimization and nonlinear programming problems. Our techniques find the optimal solution value and the optimal dual multipliers of the LP relaxation and the Lagrangean dual in polynomial time using as a subroutine either the Ellipsoid algorithm or the recent algorithm of Vaidya. Moreover, in problems of a certain structure our techniques find not only the optimal solution value, but the solution as well. Our techniques lead to significant improvements in the theoretical running time compared with previously known methods (interior point methods, Ellipsoid algorithm, Vaidya's algorithm). We use our method to the solution of the LP relaxation and the Langrangean dual of several classical combinatorial problems, like the traveling salesman problem, the vehicle routing problem, the Steiner tree problem, thek-connected problem, multicommodity flows, network design problems, network flow problems with side constraints, facility location problems,K-polymatroid intersection, multiple item capacitated lot sizing problem, and stochastic programming. In all these problems our techniques significantly improve the theoretical running time and yield the fastest way to solve them.     

一类非线性单调型方程的区域分裂法

本文考虑了一类非线性单调问题的加性Schwgrz交替法和异步平行算法,并得到了在能量模意义下的收敛性结果,最后还讨论了格式的有限元离散。     

FRANCIS QL ALGORITHM FOR FINDING THE EIGENVALUES OF ANTI-SYMMETRIC MATRICES

In this paper,we demonstrate that the double-shift QL algorithm for an irreducible anti-symmetric iridiagonal matrix with the shifts being two eigenvalues of the 2×2 matrix in the left upper corner of this matrix is convergent and the convergence rale of Ms kind of algorithm is generally cubic.     

随机扰动下三维流体界面不稳定性的并行计算

对三维流体界面不稳定性的数值模拟引进了新的数值计算方法,并在MPI并行计算环境下进行了数值模拟.利用LevelSet方法确定界面位置,零水平集对应界面位置.对应离散LevelSet方程和界面两侧的两套Euler方程,借助于Ghost网格方法来完成离散.对最后网格点上的两套状态量的辨认依赖于该点的LevelSet值的符号.并进行了数值计算.     

一维搜索的一个Anderson-Bjrck外推加速算法

对一维搜索的二点二次插值法,利用Anderson-B j rck外推的思想提出了一个加速收敛算法,得出并证明了两条收敛性定理,且通过数值试验验证了该算法比二点二次插值法收敛速度快很多。     

一种动态自适应的网格负载平衡调度算法

根据计算机网络固有的层次结构特性，提出了基于层次结构的动态自适应的网格负载平衡调度算法，在下层结点上采用便于管理的集中式算法；而在高层结点上采用高效稳定的分布式渗透算法．该算法由于在结点的重载和轻载状态之间增加了一个缓冲状态——适度，使得系统的负载状态刻画得更为精确，从而使网格系统趋于平衡稳定；另外在负载迁移时也尽量地采取就近迁移的原则，使得系统开销和网络通讯量得以减少．     

一种生成对称群S9所有Sylow-p子群的算法

根据对称群的基本性质以及第二同构定理，给出了通过添加生成元到P群来构造对称群的一个Sylow-p子群的定理，添加的生成元保证能够快速得到对称群的一个Sylow—p子群．根据第二西洛定理求出了所有共轭子群，即所有Sylow-p子群．针对求所有共轭子群过程中面临共轭子群出现重复的问题，利用正规化子的性质，找到使得两个Sylow-p子群共轭的元，保证每次求的Sylow-P子群不重复．将此算法应用于S1，实验表明该算法可操作性强，耗费时间少．     

一种求解多峰函数优化问题的演化算法

针对演化计算产生新解无序的问题，提出了基于相似性的邻域搜索策略．利用邻域搜索，可以方便地建立自适应的新解产生机制．针对演化算法设计中存在的搜索效果和效率平衡问题，提出了利用适应值对个体进行分级的搜索策略．通过对个体的分级，可以区分个体在搜索过程中的职能：优秀的个体进行局部极小值的开采；其他的个体进行搜索空间的探索，以发现新的局部极小值．数值实验表明，新算法能有效处理低维多峰函数，能找到所有的全局最优解．对高维多峰函数．也能找到全局最优解．