A Class of Revised Broyden Algorithms Without Exact Line Search

In this paper, we discuss the convergence of the Broyden algorithms with revised search direction. Under some inexact line searches, we prove that the algorithms are globally convergent for continuously differentiable functions and the rate of local convergence of the algorithms is one-step superlinear and n-step second-order for uniformly convex objective functions.     

A faster Broyden method

A variation of the Broyden update is found to require less operations and to work as well as the usual Broyden update.     

大规模无约束优化的一族LBFGS类算法

尝试在有限存储类算法中利用目标函数值所提供的信息.首先利用插值条件构造了一个新的二次函数逼近目标函数,得到了一个新的弱割线方程,然后将此弱割线方程与袁[1]的弱割线方程相结合,给出了一族包括标准LBFGS的有限存储BFGS类算法,证明了这族算法的收敛性.从标准试验函数库CUTE中选择试验函数进行了数值试验,试验结果表明这族算法的数值表现都与标准LBFGS类似.     

Broyden修正算法

对于求解非线性方程组F (x) =0的Broyden秩1方法的计算格式提出一种修正算法,尝试利用矩阵的奇异值分解求解迭代方程组,并且配合使用加速技巧,从而大大提高了算法的安全性和收敛速度.数值算例表明了新算法的有效性.     

A Class of Alternating Linearization Algorithms for Nonsmooth Convex Optimization

Acta Mathematicae Applicatae Sinica, English Series - We consider the problems of minimizing the sum of a continuously differentiable convex function and a nonsmooth convex function in this paper....     

一类组合最优化问题及其算法

本文介绍三个新的组合最优化模型，并分别给出复杂性为Ｏ（Ｎ２）和Ｏ（Ｎ２α）的多项式算法和拟多项式算法．     

一类抛物型方程初值问题的随机数值算法

本文引入了求解二阶拟线性抛物型微分方程初值问题的一类新的数值算法一分层方法,这种数值方法是通过弱显式欧拉法离散其方程解的概率表示而得到的,相应地给出了该分层方法的收敛性结果.此外,还构造了基于插值的数值算法,最后提供了数值实验,得到的数值结果验证了获得的算法的精确性和有效性.     

A Numerical Comparison of Some Modified Controlled Random Search Algorithms

In this paper we propose a new version of the Controlled Random Search(CRS) algorithm of Price. The new algorithmhas been tested on thirteen global optimization test problems. Numericalexperiments indicate that the resulting algorithm performs considerablybetter than the earlier versions of the CRS algorithms. The algorithm,therefore, could offer a reasonable alternative to many currently availablestochastic algorithms, especially for problems requiring direct searchtype methods. Also a classification of the CRS algorithms is made based onglobal technique – local technique and the relative performance ofclasses is numerically explored.     

一类改进BFGS算法及其收敛性分析

本文针对无约束最优化问题,基于目标函数的局部二次模型近似,提出一类改进的BFGS算法,称为 MBFGS算法。其修正 B_k的公式中含有一个参数θ∈[0,l],当 θ= 1时即得经典的BFGS公式;当θ∈[0、l）时,所得公式已不属于拟Newton类。在目标函数一致凸假设下,证明了所给算法的全局收敛性及局部超线性收敛性。     

求解非线性规划问题的一类对偶算法

本文提出了一类求解不等式约束非线性规划问题的构造性对偶算法,我们证明在适当的条件下,势函数的罚参数存在一个阀值,当罚参数小于这个阀值时,由这一方法所产生的序列局部收敛于问题的一个Kuhn-Tucker解,我们也建立了解的依赖于罚参数的误差上界,最后,我们给出了一个特残势函数的数值结果。     

A Class of Infeasible Interior Point Algorithms for Convex Quadratic Programming

This article proposes a class of infeasible interior point algorithms for convex quadratic programming, and analyzes its complexity. It is shown that this algorithm has the polynomial complexity. Its best complexity is O(nL).     

A Class of Large-Update and Small-Update Primal-Dual Interior-Point Algorithms for Linear Optimization

In this paper we present a class of polynomial primal-dual interior-point algorithms for linear optimization based on a new class of kernel functions. This class is fairly general and includes the classical logarithmic function, the prototype self-regular function, and non-self-regular kernel functions as special cases. The analysis of the algorithms in the paper follows the same line of arguments as in Bai et al. (SIAM J. Optim. 15:101–128, [2004]), where a variety of non-self-regular kernel functions were considered including the ones with linear and quadratic growth terms. However, the important case when the growth term is between linear and quadratic was not considered. The goal of this paper is to introduce such class of kernel functions and to show that the interior-point methods based on these functions have favorable complexity results. They match the currently best known iteration bounds for the prototype self-regular function with quadratic growth term, the simple non-self-regular function with linear growth term, and the classical logarithmic kernel function. In order to achieve these complexity results, several new arguments had to be used. This research is partially supported by the grant of National Science Foundation of China 10771133 and the Program of Shanghai Pujiang 06PJ14039.     

Structure-Preserving Algorithms for a Class of Dynamical Systems

In this paper,we study structure-preserving algorithms for dynamical systems defined by ordinarydifferential equations in R~n.The equations are assumed to be of the form y~·=A(y) D(y) R(y),where A(y)is the conservative part subject to     

Modified Partial-Update Newton-Type Algorithms for Unary Optimization

In this paper, we propose two modified partial-update algorithms for solving unconstrained unary optimization problems based on trust-region stabilization via indefinite dogleg curves. The two algorithms partially update an approximation to the Hessian matrix in each iteration by utilizing a number of times the rank-one updating of the Bunch–Parlett factorization. In contrast with the original algorithms in Ref. 1, the two algorithms not only converge globally, but possess also a locally quadratic or superlinear convergence rate. Furthermore, our numerical experiments show that the new algorithms outperform the trust-region method which uses the partial update criteria suggested in Ref. 1.     

一类求解常微分方程数值解的块方法

本文讨论了一类并行计算常微分方程初值问题的带有高阶导数的块隐式混合单步方法，这种方法可以在Ｋ台处理机上并行进行数值计算，本文对方法的一般性质及收敛性进行了讨论，得知该方法的阶数为２ｌ＋１，并且指出当ｌ＝１，２时，方法是Ａ－稳定的，最后给出了一个数值例子。     

一类锥模型非单调信赖域算法及收敛性分析

本文对无约束优化问题提出了一类基于锥模型的非单调信赖域算法.二次模型非单调信赖域算法是新算法的特例.在适当的条件下,证明了算法的全局收敛性及Q-二次收敛性.     

集值混合变分不等式的一类自适应惯性投影次梯度算法

本文在实Hilbert空间上引入了一类求解集值混合变分不等式新的自适应惯性投影次梯度算法.在集值映射T为f-强伪单调或单调的条件下,我们证明了由该自适应惯性投影次梯度算法所产生的序列强收敛于集值混合变分不等式问题的的唯一解.     

求解一类非线性方程的改进的平均法

本文研究确定非线性方程一致有效近似解的平均法,得到B方法(Krylov-Bogoliubov method)与KBM方法(Krylov-Bogoliubov-Mitropolski method)的改进形式,通过两个例子与多尺度方法的比较,说明改进的平均法的有效性,从而拓广了平均法的应用范围。     

一类二次半定规划内点算法的搜索方向

利用牛顿法求解一类二次半定规划的扰动KKT方程组,得出这类二次半定规划原始-对偶路径跟踪算法搜索方向求解的统一形式,以及HKM搜索方向和NT搜索方向存在唯一的充分条件,最后给出了计算搜索方向的表达式,和特殊情况下搜索方向的计算方法.