一种改进的Adomian分解方法

给出了一种新的改进Adomian分解方法,新方法能有效地解决传统Adomian分解方法及其改进方法的不足.将新改进方法应用于第二类Volterra积分方程、积分-微分方程求解,并与传统Adomian分解方法及其改进方法作比较分析,结果表明提出的新改进方法能返回方程精确解析解.     

解分数阶微分代数系统的Adomian分解方法

研究了利用Adomian分解求解分数阶微分代数系统的方法.分析了代数约束对Adomian方法求解的影响,指出直接解出代数约束变量,将原系统转化为微分系统进行Adomian分解的困难.提出确定代数变量级数解各分量的新方法,据此进行Adomian分解,得到整个系统的级数解.特别研究了代数约束为线性的分数阶微分代数系统的Adomian解法,证明了各变量间的线性代数约束关系可以转化为相应级数解中各分量的线性关系,从而方便求解,并结合具体例子证明了该方法简便有效.     

有限区域求解流函数和速度势的迭代调整方法及其收敛性分析

全球区域求解流函数和速度势的解是唯一的,但有限区域内,由于受区域边界条件限制,流函数和速度势的计算以及风场的分解不是唯一的,减小或消除边界不确定对结果的影响是有限区域求解流函数和速度势以及分解风场最重要的问题．该文在Endlich迭代调整思想上,提出了能准确求解有限区域流函数和速度势且对边界条件要求较低的迭代调整方法．该方法也能准确地分解和重建风场,且风场重建的误差非常小．对该迭代方法的收敛性进行分析,发现其收敛性与不同方向网格的格距和调整系数有关．最后将该方法应用到Arakawa A-D网格和不规则区域,验证了该方法的可靠性．     

云计算在RSA密码体制分析中的应用

RSA是著名的公钥密码体制之一,其安全性是基于大整数因子分解困难性假设的,求解RSA问题的最直接方法是分解RSA的模数.由于云计算的大规模分布式计算能力,一些使用分布式计算模型MapReduce的大整数分解手段已经实现,针对大整数因子分解的问题,提出了给定范围内搜索因子的新方法,并对相应的实验数据和结果进行了分析.结果表明,在云中的分布式计算的运行时间远小于单台机器.     

符号几何规划的一种分解方法

针对符号几何规划提出了一种直接的分解方法,将难于求解的符号几何规划问题等价地转化为一个非线性程度很低的可分离规划,为寻求困难度高且规模较大的符号几何规划问题的求解提供了一种方法,特别是经此方法分解后的每个子问题均易于求解,最后给出了数值实例,验证了此方法的有效性．     

Navier-Stokes方程的一种并行两水平有限元方法

基于区域分解技巧,提出了一种求解定常Navier-Stokes方程的并行两水平有限元方法．该方法首先在一粗网格上求解Navier-Stokes方程,然后在细网格的子区域上并行求解粗网格解的残差方程,以校正粗网格解．该方法实现简单,通信需求少．使用有限元局部误差估计,推导了并行方法所得近似解的误差界,同时通过数值算例,验证了其高效性．     

一种新的声椭球无限单元

提出了一种新的声椭球无限单元．这种声无限单元基于一种新的声压表达式,这种声压表达式能够更准确地代表着椭球声场的声传播模式．这种新方法的形函数类似于Burnett方法,而权函数定义为形函数和一个附加因子的乘积．因为仅需要一维的数值积分,这种新方法的代码生成十分容易,就像处理一维单元一样．耦合标准的有限元程序,这种声无限单元理论上能够高效地求解任何形状的声源的声辐射和声散射现象．简要地推导了这种新方法,并给出了这种方法详尽的推导结果．为更有效地检验该无限元方法的可行性,文中例子仅考虑无限元求解的精度,而不包括相应的有限元．使用这种新方法,精确地推导出了摆动球的理论计算公式．而长旋转椭球的例子则表明了这种方法优于边界元方法和其他声椭球无限元方法．这些例子表明了这种新方法是切实可行的．     

基于变分法对一类非线性扩散方程解析解研究北大核心CSCD

本文分别针对一类扩散系数为非线性指数函数和幂函数的扩散方程,基于变分原理中的泛函极值理论分别提出了求解该方程Dirichlet边界和Neumann边界问题解析解的新方法,并证明了新方法是泛函问题极值解的充要性．以非饱和土壤水分运动问题为背景,给出了积水和恒通量条件下水平吸渗问题的解析解,并通过数值算例将解析解与数值解进行了比较分析,结果表明本文方法得到的解析解能够准确预测非饱和土壤水分水平吸渗问题的土壤含水量分布,是一种有效方法．因此本文方法为求解这一类非线性扩散方程提供了一种有效的新方法．     

求解热传导反问题的一种正则化Newton型迭代法

讨论热传导方程求解系数的一个反问题．把问题归结为一个非线性不适定的算子方程后,考虑该方程的Newton型迭代方法．对线性化后的Newton方程用隐式迭代法求解,关键的一步是引入了一种新的更合理的确定(内)迭代步数的后验准则．对新方法及对照的Tikhonov方法和Bakushiskii方法进行了数值实验,结果显示了新方法具有明显的优越性．     

正规升列在参数代数方程组求解中的应用

本文提出一种利用多项式系统的正规零点分解的算法来求解代数方程组以及带有参数的代数方程组的方法．对于给定的的代数方城组,通过正规分解,可以得到一组具有三角形式的分解．根据这种三角形式,我们可以给出代数方程组的所有解．而对于带有参数方程组,将给出方程组有解时参数需满足的条件．进一步,对于给定的参数值,正规分解中得到三角形式仍然保持,通过求解三角形式的方程组从而得出原参数方程组的解．     

A new criterion for the inexact logarithmic-quadratic proximal method and its derived hybrid methods

To solve nonlinear complementarity problems, the inexact logarithmic-quadratic proximal (LQP) method solves a system of nonlinear equations (LQP system) approximately at each iteration. Therefore, the efficiencies of inexact-type LQP methods depend greatly on the involved inexact criteria used to solve the LQP systems. This paper relaxes inexact criteria of existing inexact-type LQP methods and thus makes it easier to solve the LQP system approximately. Based on the approximate solutions of the LQP systems, a descent method, and a prediction–correction method are presented. Convergence of the new methods are proved under mild assumptions. Numerical experiments for solving traffic equilibrium problems demonstrate that the new methods are more efficient than some existing methods and thus verify that the new inexact criterion is attractive in practice.     

P_0函数非线性互补问题的一步非内点连续方法的收敛性

本文对于Ｐ０函数非线性互补问题提出了一个基于Ｋａｎｚｏｗ光滑函数的一步非内点连续方法,在适当的假设条件下,证明了方法的全局线性及局部二次收敛性．特别,在方法的全局线性收敛性的分析中,不需要假定非线性互补问题的函数的Ｊａｃｏｂｉ阵是Ｌｉｐｓｃｈｉｔｚ连续的．文献中为了得到非内点连续方法的全局线性收敛性,这一假定是被广泛使用的．本文提出的方法在每一次迭代只须解一个线性方程式组．     

A heuristic algorithm for constrained multi-source Weber problem – The variational inequality approach

For solving the well-known multi-source Weber problem (MWP), each iteration of the heuristic alternate location–allocation algorithm consists of a location phase and an allocation phase. The task of the location phase is to solve finitely many single-source Weber problems (SWP), which are reduced by the heuristic of nearest center reclassification for the customers in the previous allocation phase. This paper considers the more general and practical case – the MWP with constraints (CMWP). In particular, a variational inequality approach is contributed to solving the involved constrained SWP (CSWP), and thus a new heuristic algorithm for CMWP is presented. The involved CSWP in the location phases are reformulated into some linear variational inequalities, whose special structures lead to a new projection–contraction (PC) method. Global convergence of the PC method is proved under mild assumptions. The new heuristic algorithm using the PC method in the location phases approaches to the heuristic solution of CMWP efficiently, which is verified by the preliminary numerical results reported in this paper.     

Subordination and superordination results for analytic functions with respect to symmetrical points

The theory of symmetric functions has many applications in the investigation of fixed points, estimation of absolute values of some integrals and obtaining the results of the type of Cartan’s uniqueness theorem. In this paper, we solve some differential subordinations and superordinations involving analytic functions with respect to the symmetric points and also derive some sandwich results under certain assumptions on the parameters involved. The various results presented in this paper are shown to apply to yield the corresponding (new or known) results for many simpler function classes.     

An exponential penalty method for nondifferentiable minimax problems with general constraints

A well-known approach to constrained minimization is via a sequence of unconstrained optimization computations applied to a penalty function. This paper shows how it is possible to generalize Murphy's penalty method for differentiable problems of mathematical programming (Ref. 1) to solve nondifferentiable problems of finding saddle points with constraints. As in mathematical programming, it is shown that the method has the advantages of both Fiacco and McCormick exterior and interior penalty methods (Ref. 2). Under mild assumptions, the method has the desirable property that all trial solutions become feasible after a finite number of iterations. The rate of convergence is also presented. It should be noted that the results presented here have been obtained without making any use of differentiability assumptions.     

随机ADMM算法及其在电力系统凸经济调度问题中的应用

针对电力系统中的一类凸经济调度问题,提出了随机ADMM算法,设计了周期循环更新规则和随机选择更新规则,证明了随机ADMM算法在周期循环更新规则下的收敛性,以及得出了在随机选择更新规则下按期望收敛的结论.数值实验结果表明该方法可以有效解决电力系统中的凸经济调度问题.     

不确定情况下的一类递归效用优化问题(英文)

本文通过对倒向随机微分方程进行摄动的方法研究了金融市场中最优投资组合和消费选择问题．在没有凸性假设下,用Ｅｋｌａｎｄ 变分原理解决了这个带初始约束的优化问题     

A fixed point method for the linear complementarity problem arising from american option pricing

For American option pricing, the Black-Scholes-Merton model can be discretized as a linear complementarity problem (LCP) by using some finite difference schemes. It is well known that the Projected Successive Over Relaxation (PSOR) has been widely applied to solve the resulted LCP. In this paper, we propose a fixed point iterative method to solve this type of LCPs, where the splitting technique of the matrix is used. We show that the proposed method is globally convergent under mild assumptions. The preliminary numerical results are reported, which demonstrate that the proposed method is more accurate than the PSOR for the problems we tested.     

On an initial inverse problem in nonlinear heat equation associated with time-dependent coefficient

In this paper, a nonlinear backward heat problem with time-dependent coefficient in the unbounded domain is investigated. A modified regularization method is established to solve it. New error estimates for the regularized solution are given under some assumptions on the exact solution.     

An improved proximal alternating direction method for monotone variational inequalities with separable structure

To solve a class of variational inequalities with separable structure, this paper presents a new method to improve the proximal alternating direction method (PADM) in the following senses: an iterate generated by the PADM is utilized to generate a descent direction; and an appropriate step size along this descent direction is identified. Hence, a descent-like method is developed. Convergence of the new method is proved under mild assumptions. Some numerical results demonstrate that the new method is efficient.