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1.
本文提供了一簇新的过滤线搜索修正正割方法求解非线性等式约束优化问题.新算法簇的特点是:用修正正割算法簇中的一个算法获得搜索方向,回代线搜索技术得到步长,过滤准则用来决定是否接受步长,引入二阶校正技术减少不可行性并克服Maratos效应.在合理的假设条件下,分析了算法的总体收敛性.并证明了,通过附加二阶校正步,算法簇克服了Maratos效应,并二步Q-超线性收敛到满足二阶充分最优条件的局部解.数值结果表明了所提供的算法具有有效性.  相似文献   

2.
提出了结合仿射尺度技术的正割算法解非线性等式与有界约束优化问题.在合理假设下,证明了渐弱滤子线搜索方法可以保证新算法具有整体收敛性.通过引入一个高阶修正方向,克服Maratos效应的影响,使得算法二步q-超线性收敛于最优点.进一步地,对算法进行修改,使得新算法达到q-超线性收敛性.  相似文献   

3.
提出了结合仿射尺度技术的正割算法解非线性等式与有界约束优化问题. 在合理假设下, 证明了渐弱滤子线搜索方法可以保证新算法具有整体收敛性. 通过引入一个高阶修正方向, 克服Maratos效应的影响, 使得算法二步$q$-\!\!超线性收敛于最优点. 进一步地, 对算法进行修改, 使得新算法达到$q$-\!\!超线性收敛性.  相似文献   

4.
提出了使用硬阈值进行矩阵填充的修正算法.算法通过对迭代矩阵进行对角修正来完成矩阵填充,并给出了算法的收敛性分析.最后通过数值实验比较了修正算法与硬阈值算法填充的数值结果,显示出了新算法的优越性.  相似文献   

5.
引入多个参数,利用正割函数的有理分式展开形式,建立了一个最佳常数因子与正割函数的偶数阶导数有关的,并定义在R×R上的Hilbert型积分不等式及其等价形式.特别地,赋予参数不同的数值,文末还建立了一些特殊的Hilbert型不等式.  相似文献   

6.
本文对凸函数在极值点的Hessian矩阵是秩亏一的情况下,给出了一类求解无约束优化问题的修正BFGS算法.算法的思想是对凸函数加上一个修正项,得到一个等价的模型,然后简化此模型得到一个修正的BFGS算法.文中证明了该算法是一个具有超线性收敛的算法,并且把修正的BFGS算法同Tensor方法进行了数值比较,证明了该算法对求解秩亏一的无约束优化问题更有效.  相似文献   

7.
朱德通 《应用数学》1999,12(2):65-71
基于Powell和Yuan所建议的近似Fetcher罚函数作为函数使用单调线搜索的技术,本文提供了一类正割方法解约束优化。在合理的条件下,证明了所提供的算法的整体收敛性和收敛速率。  相似文献   

8.
基于Toeplitz矩阵填充(TMC)的修正增广拉格朗日乘子(MALM)算法,本文给出此算法的一种加速策略,提出Toeplitz矩阵填充的?-步修正增广拉格朗日乘子算法.该方法通过削减原MALM算法中每一步迭代的频繁数据传输,提高算法的运行效率.同时也证明了新算法的收敛性.最后以数值实验表明?-步修正增广拉格朗日乘子算法比原MALM算法更有效.  相似文献   

9.
温瑞萍  李姝贞 《应用数学》2019,32(4):887-899
基于 Toeplitz矩阵填充(TMC)的修正增广拉格朗日乘子(MALM)算法, 本文给出此算法的一种加速策略, 提出Toeplitz矩阵填充的 $\ell$-步修正增广拉格朗日乘子算法. 该方法通过削减原 MALM算法中每一步迭代的频繁数据传输, 提高算法的运行效率. 同时也证明了新算法的收敛性. 最后以数值实验表明 $\ell$-步修正增广拉格朗日乘子算法比原 MALM算法更有效.  相似文献   

10.
对闭凸集约束的非线性规划问题构造了一个修正共轭梯度投影下降算法,在去掉迭代点列有界的条件下,分析了算法的全局收敛性.新算法与共轭梯度参数结合,给出了三类结合共轭梯度参数的修正共轭梯度投影算法.数值例子表明算法是有效的.  相似文献   

11.
The secant method is one of the most popular methods for root finding. Standard text books in numerical analysis state that the secant method is superlinear: the rate of convergence is set by the gold number. Nevertheless, this property holds only for simple roots. If the multiplicity of the root is larger than one, the convergence of the secant method becomes linear. This communication includes a detailed analysis of the secant method when it is used to approximate multiple roots. Thus, a proof of the linear convergence is shown. Moreover, the values of the corresponding asymptotic convergence factors are determined and are found to be also related with the golden ratio.  相似文献   

12.
§ 1  IntroductionWe consider the following equality contrained minimization problem:minf(x)s.t.c(x) =0 , (1 .1 )wheref :Rn→ R1 and c:Rn→ Rmare twice continuously differentiable.In[1 ] ,Fontecilla proposed the secant methods and proved their localq -superlineartwo-step convergence property under certain conditions.However,the global convergenceis not concerned in this paper,since Fontecilla did not discuss the important question ofensuring progress towards the solution of the problem(1 .1…  相似文献   

13.
Abstract. The secant methods discussed by Fontecilla (in 1988) are considerably revised through employing a trust region multiplier strategy and introducing a nondifferentiable merit function, In this paper the secant methods are also improved by adding a dogleg typed movement which allows to overcome a phenomena similar to the Maratos effect. Furthermore, these algorithms are analyzed and global convergence theorems as well as local superlinear conver-gence rate are proved.  相似文献   

14.
In this paper, an inexact secant algorithm in association with nonmonotone technique and filter is proposed for solving the large scale nonlinear systems of equalities and inequalities. The systems are transformed into a continuous constrained optimization solved by inexact secant algorithm. Global convergence of the proposed algorithm is established under the reasonable conditions. Numerical results validate the effectiveness of our approach.  相似文献   

15.
Filter methods were initially designed for nonlinear programming problems by Fletcher and Leyffer. In this paper we propose a secant algorithm with line search filter method for nonlinear equality constrained optimization. The algorithm yields the global convergence under some reasonable conditions. By using the Lagrangian function value in the filter we establish that the proposed algorithm can overcome the Maratos effect without using second order correction step, so that fast local superlinear convergence to second order sufficient local solution is achieved. The primary numerical results are presented to confirm the robustness and efficiency of our approach.  相似文献   

16.
For solving unconstrained minimization problems, quasi-Newton methods are popular iterative methods. The secant condition which employs only the gradient information is imposed on these methods. Several researchers paid attention to other secant conditions to get a better approximation of the Hessian matrix of the objective function. Recently, Zhang et al. [New quasi-Newton equation and related methods for unconstrained optimization, J. Optim. Theory Appl. 102 (1999) 147–167] and Zhang and Xu [Properties and numerical performance of quasi-Newton methods with modified quasi-Newton equations, J. Comput. Appl. Math. 137 (2001) 269–278] proposed the modified secant condition which uses both gradient and function value information in order to get a higher order accuracy in approximating the second curvature of the objective function. They showed the local and q-superlinear convergence property of the BFGS-like and DFP-like updates based on their proposed secant condition. In this paper, we incorporate one parameter into this secant condition to smoothly switch the standard secant condition and the secant condition of Zhang et al. We consider a modified Broyden family which includes the BFGS-like and the DFP-like updates proposed by Zhang et al. We prove the local and q-superlinear convergence of our method.  相似文献   

17.
《Optimization》2012,61(12):2229-2246
ABSTRACT

A secant equation (quasi-Newton) has one of the most important rule to find an optimal solution in nonlinear optimization. Curvature information must satisfy the usual secant equation to ensure positive definiteness of the Hessian approximation. In this work, we present a new diagonal updating to improve the Hessian approximation with a modifying weak secant equation for the diagonal quasi-Newton (DQN) method. The gradient and function evaluation are utilized to obtain a new weak secant equation and achieve a higher order accuracy in curvature information in the proposed method. Modified DQN methods based on the modified weak secant equation are globally convergent. Extended numerical results indicate the advantages of modified DQN methods over the usual ones and some classical conjugate gradient methods.  相似文献   

18.
Secant methods for semismooth equations   总被引:1,自引:0,他引:1  
Some generalizations of the secant method to semismooth equations are presented. In the one-dimensional case the superlinear convergence of the classical secant method for general semismooth equations is proved. Moreover a new quadratically convergent method is proposed that requires two function values per iteration. For the n-dimensional cases, we discuss secant methods for two classes of composite semismooth equations. Most often studied semismooth equations are of such form. Received October 16, 1996 / Revised version received July 25, 1997  相似文献   

19.
Conjugate gradient methods are appealing for large scale nonlinear optimization problems. Recently, expecting the fast convergence of the methods, Dai and Liao (2001) used secant condition of quasi-Newton methods. In this paper, we make use of modified secant condition given by Zhang et al. (1999) and Zhang and Xu (2001) and propose a new conjugate gradient method following to Dai and Liao (2001). It is new features that this method takes both available gradient and function value information and achieves a high-order accuracy in approximating the second-order curvature of the objective function. The method is shown to be globally convergent under some assumptions. Numerical results are reported.  相似文献   

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