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.     

基于混合细菌趋药性的聚类分割算法

为解决模糊C均值算法对初始值敏感、容易陷入局部极值的问题,提出基于混合细菌趋药性的聚类分割算法,在简单细菌趋药性算法的基础上,将粒子群算法引入.新算法使用粒子群算法、细菌趋药性算法两步优化得到的结果作为模糊C均值算法的初始值,同时新算法中引入精英保持策略,进一步提高算法效率.实验结果表明,新算法具有较快的收敛速度,.同时能够获得较好的图像分割效果和质量.     

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.     

求解广义鞍点问题的一个新的类SOR算法

本文提出了求解广义鞍点问题的一个新的类SOR迭代算法,并分析了新算法的收敛性.数值实验结果表明新算法是十分有效的.     

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.     

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.     

推广AS-GN混合共轭梯度算法

本文提出了一种求解无约束优化问题的新算法,使Touati-Ahmed, Storey提出的混合共轭梯度法(以下简称AS)和Gilbert, Nocedal提出的混合共轭梯度法(以下简称GN)成为新算法在精确线性搜索下的特例.通过构造新的$\beta_{k}$计算公式,新算法自然满足下降性条件,且这个性质与线性搜索和目标函数的凸性均无关.在一般的条件下,我们证明了新算法的全局收敛性.数值结果表明该算法对测试函数是有效的.     

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.     

解线性等式约束优化问题的模式搜索过滤集方法（英文）

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.     

一种基于邻近点算法的变步长原始-对偶算法

本文考虑求解一种源于信号及图像处理问题的鞍点问题.基于邻近点算法的思想,我们对原始-对偶算法进行改进,构造一种对称正定且可变的邻近项矩阵,得到一种新的原始-对偶算法.新算法可以看成一种邻近点算法,因此它的收敛性易于分析,且无需较强的假设条件.初步实验结果表明,当新算法被应用于求解图像去模糊问题时,和其他几种主流的高效算法相比,新算法能得到较高质量的结果,且计算时间也是有竞争力的.     

一种混合的HS-DY共轭梯度法

本文在HS方法和DY方法的基础上,综合两者的优势,提出了一种求解无约束优化问题的新的混合共轭梯度法.在Wolfe线搜索下,不需给定下降条件,证明了算法的全局收敛性.数值试验表明,新算法较之HS方法和PR方法更加有效.     

A Krylov-Schur-like method for computing the best rank-(r1,r2,r3) approximation of large and sparse tensors

Numerical Algorithms - The paper is concerned with methods for computing the best low multilinear rank approximation of large and sparse tensors. Krylov-type methods have been used for this...     

Efficient preconditioners for Radau-IIA time discretization of space fractional diffusion equations

Numerical Algorithms - This paper is concerned with the construction of efficient preconditioners for systems arising from implicit Runge-Kutta time discretization methods for one-dimensional and...     

Optimization of nearest neighbor classifiers via metaheuristic algorithms for credit risk assessment

The classification problem consists of using some known objects, usually described by a large vector of features, to induce a model that classifies others into known classes. The present paper deals with the optimization of Nearest Neighbor Classifiers via Metaheuristic Algorithms. The Metaheuristic Algorithms used include tabu search, genetic algorithms and ant colony optimization. The performance of the proposed algorithms is tested using data from 1411 firms derived from the loan portfolio of a leading Greek Commercial Bank in order to classify the firms in different groups representing different levels of credit risk. Also, a comparison of the algorithm with other methods such as UTADIS, SVM, CART, and other classification methods is performed using these data.     

Investigations on several high-order ADI methods for time-space fractional diffusion equation

Numerical Algorithms - The paper is devoted to the construction of high-precision unconditionally stable finite difference methods for solving time-space fractional diffusion equation with the...     

Generalized second derivative linear multistep methods for ordinary differential equations

Numerical Algorithms - This paper is devoted to investigate the modified extended second derivative backward differentiation formulae from second derivative general linear methods point of view....     

On block Gaussian sketching for the Kaczmarz method

Numerical Algorithms - The Kaczmarz algorithm is one of the most popular methods for solving large-scale over-determined linear systems due to its simplicity and computational efficiency. This...     

Boundary Value Problems for Systems of Functional Differential Equations

Algorithms for finding an approximate solution of boundary value problems for systems of functional ordinary differential equations are studied. Sufficient conditions for consistency and convergence of these methods are given. In the last section, a construction of methods of arbitrary order is presented.     

Explicit pseudo two-step exponential Runge–Kutta methods for the numerical integration of first-order differential equations

Numerical Algorithms - This paper is devoted to the explicit pseudo two-step exponential Runge–Kutta (EPTSERK) methods for the numerical integration of first-order ordinary differential...     

Asynchronous Richardson iterations: theory and practice

Numerical Algorithms - We consider asynchronous versions of the first- and second-order Richardson methods for solving linear systems of equations. These methods depend on parameters whose values...