非线性互补问题的两种数值解法

本文研究了非线性互补问题的两类数值求解方法.在经典LQP算法及LevenbergMarquardt算法的基础上,构造了两种新算法,并证明了这两种新算法的收敛性.数值实验表明,新算法对测试问题优于已有算法.     

计算Adomian多项式的新算法

本文给出了一个计算Adomian多项式的新算法,并将其用于求微分方程的近似 解.我们的算法比原有算法效率高,且易于在计算机上实现.我们在Maple中实现了这一 算法,并通过30多个微分方程的求解验证了新算法的有效性.     

Kth最短路径的Bellman改进算法

基于对Bellm an算法的改进,得到了求解k th最短路的新算法.改进算法的优势在于从Bellm an算法只能解决最短路问题拓展到求解k th最短路问题,而且可以考虑权重为负数的情况.与传统算法相比,新算法更易于理解.     

一类具有非单调线搜索的混合共轭梯度算法

提出一类求解无约束最优化问题的混合共轭梯度算法,新算法有机地结合了DY算法和HS算法的优点,并采用非单调线搜索技术在较弱条件下证明了算法的全局收敛性.数值实验表明新算法具有良好的计算效能.     

递减率的一种宏观改进算法

在对沈采实际区块进行油藏工程评价过程中,在对原有的综合递减率算法进行分析总结基础上对其进行了优化,提出了更具有宏观性的新算法.新算法克服了原油算法所受影响因素较多的特点,只与评价的递减区间端点的年产油量和区间长度有关.新算法降低了年产油量的波动对参数结果的影响,进而增强了对油田整体生产情况的把握分析能力,更准确地反应了油田的现状,进一步为油田区块今后的开发方案的调整与部署提供参考依据.新算法的优越性最后通过现场实例得到了验证.     

基于凸组合共轭梯度法的ARIMA模型参数估计

提出了一种凸组合共轭梯度算法,并将其算法应用到ARIMA模型参数估计中.新算法由改进的谱共轭梯度算法与共轭梯度算法作凸组合构造而成,具有下述特性:1)具备共轭性条件;2)自动满足充分下降性.证明了在标准Wolfe线搜索下新算法具备完全收敛性,最后数值实验表明通过调节凸组合参数,新算法更加快速有效,通过具体实例证实了模型的显著拟合效果.     

广义鞍点问题的改进的类SOR算法

针对广义鞍点问题,本文提出了一个改进的类逐次超松弛迭代算法,在较弱的条件下,分析了算法的收敛性及线性收敛率.新算法的每步计算量与已有的算法类似,都是需要（近似）求解线性方程组,但新算法有更好的灵活度通过合适地选取参数矩阵,每一步子问题可以容易地求解,甚至可以有闭式解（closed-form solution）.数值实验结果显示了新算法的有效性.     

解线性等式约束优化问题的模式搜索过滤集方法

提出一个解线性等式约束无导数优化的模式搜索过滤集算法,该算法将过滤集技术嵌入无导数优化算法中以改善算法的效率. 建立了新算法的总体收敛性, 初步的数值试验结果表明新算法是有效的.     

基于最小调整法求解旅行商问题

介绍了一种求解旅行商问题的新算法"最小调整法",给出了该算法求解旅行商问题的具体步骤以及有效性证明,对算法的复杂性及近似程度进行了分析.最后通过典型算例进行了检验说明.与经典算法相比,新算法体现了简单易行的特点,对求解旅行商问题具有一定的启发意义.     

一种求解非线性互补问题的filter内点算法

利用Armijio条件和信赖域方法,构造新的价值函数.首次将内点算法与filter技术结合起来,提出一种求解非线性互补问题的新算法,即filter内点算法.在主算法中使用Armijio型线搜索求取步长,在修复算法中使用信赖域方法进行适当控制以保证算法的收敛性.文章还讨论了算法的全局收敛性.最后用数值实验表明了该方法是有效的.     

求解块三对角方程组的新算法

根据块三对角矩阵的特殊分解,给出了求解块三对角方程组的新算法.该算法含有可以选择的参数矩阵,适当选择这些参数矩阵,可以使得计算精度较著名的追赶法高,甚至当追赶法失效时,由该算法仍可得到一定精度的解.     

Analysis of a new parareal algorithm based on waveform relaxation method for time-periodic problems

We present a new parallel algorithm for time-periodic problems by combining the waveform relaxation method and the parareal algorithm, which performs the parallelism both in sub-systems and in time. In the new algorithm, the waveform relaxation propagator is chosen as a new fine propagator instead of the classical fine propagator. And because of the characteristic of time-periodic problems, the new parareal waveform relaxation algorithm needs to solve a periodic coarse problem at the coarse level in each iteration. The new algorithm is proved to converge linearly at most. Then the theoretic parallel efficiency of the new algorithm is also considered. Numerical experiments confirm our analysis finally.     

一个新的线性规划无人工变量算法

本文研究了线性规划的求解问题.利用对偶转化的方法,获得了一个计算效率高的新的无人工变量通用算法.该新算法比最近提出的无人工变量算法push-to-pull算法效率更高.     

关于解极大相关问题P-SOR算法的收敛性

对求解极大相关问题的P-SOR方法的收敛性做了进一步研究.得到了一些新的收敛条件.为了提高收敛到全局最大解的可能性,提出了一种新的初始向量选择策略.给出了P-SOR算法的对称形式(P-SSOR).还给出了一种算法精化策略.最后,用数值例子说明新方法的有效性.     

A mean value algorithm for Toeplitz matrix completion

In this paper, we propose a new mean value algorithm for the Toeplitz matrix completion based on the singular value thresholding (SVT) algorithm. The completion matrices generated by the new algorithm keep a feasible Toeplitz structure. Meanwhile, we prove the convergence of the new algorithm under some reasonal conditions. Finally, we show the new algorithm is much more effective than the ALM (augmented Lagrange multiplier) algorithm through numerical experiments and image inpainting.     

The global and superlinear convergence of a new nonmonotone MBFGS algorithm on convex objective functions

In this paper, a new nonmonotone MBFGS algorithm for unconstrained optimization will be proposed. Under some suitable assumptions, the global and superlinear convergence of the new nonmonotone MBFGS algorithm on convex objective functions will be established. Some numerical experiments show that this new nonmonotone MBFGS algorithm is competitive to the MBFGS algorithm and the nonmonotone BFGS algorithm.     

A gradient-related algorithm with inexact line searches

In this paper, a new gradient-related algorithm for solving large-scale unconstrained optimization problems is proposed. The new algorithm is a kind of line search method. The basic idea is to choose a combination of the current gradient and some previous search directions as a new search direction and to find a step-size by using various inexact line searches. Using more information at the current iterative step may improve the performance of the algorithm. This motivates us to find some new gradient algorithms which may be more effective than standard conjugate gradient methods. Uniformly gradient-related conception is useful and it can be used to analyze global convergence of the new algorithm. The global convergence and linear convergence rate of the new algorithm are investigated under diverse weak conditions. Numerical experiments show that the new algorithm seems to converge more stably and is superior to other similar methods in many situations.     

An alternative to the Bathe algorithm

This paper presents a new composite sub-steps algorithm for solving reliable numerical responses in structural dynamics. The newly developed algorithm is a two sub-steps, second-order accurate and unconditionally stable implicit algorithm with the same numerical properties as the Bathe algorithm. The detailed analysis of the stability and numerical accuracy is presented for the new algorithm, which shows that its numerical characteristics are identical to those of the Bathe algorithm. Hence, the new sub-steps scheme could be considered as an alternative to the Bathe algorithm. Meanwhile, the new algorithm possesses the following properties: (a) it produces the same accurate solutions as the Bathe algorithm for solving linear and nonlinear problems; (b) it does not involve any artificial parameters and additional variables, such as the Lagrange multipliers; (c) The identical effective stiffness matrices can be obtained inside two sub-steps; (d) it is a self-starting algorithm. Some numerical experiments are given to show the superiority of the new algorithm and the Bathe algorithm over the dissipative CH-α algorithm and the non-dissipative trapezoidal rule.     

A flexible CMRH algorithm for nonsymmetric linear systems

A flexible version of the CMRH algorithm is presented that allows varying preconditioning at every step of the algorithm. A consequence of the flexibility of this new variant is that any iterative methods can be incorporated as a preconditioner in the inner steps. Theoretical results that relate the residual norm of the new algorithm and the flexible GMRES, the new algorithm with CMRH itself, are given. Numerical experiments are carried out to illustrate the effectiveness of the proposed algorithm in comparison with the standard CMRH algorithm, ILU-preconditioned CMRH variants and the flexible GMRES algorithm.     

H∞强镇定问题的新解法

H∞强镇定问题可解的原始算法是依赖于一个解存在的充分条件．自然的此算法应用起来有一定的局限性．针对此问题，首先给出H∞强镇定问题可解的一个充要条件．并说明该条件在计算上很容易实现的．并由此充要条件出发设计了一个简单且实际可行的算法．该算法实际上没有局限性，而且比较利于计算机编程．最后举例说明新算法与H∞强镇定问题可解的原有算法相比，具有更大的优点．