共查询到20条相似文献,搜索用时 31 毫秒
1.
倪勤 《高等学校计算数学学报(英文版)》1997,(1)
In this paper we report a sparse truncated Newton algorithm for handling large-scale simple bound nonlinear constrained minimixation problem. The truncated Newton method is used to update the variables with indices outside of the active set, while the projected gradient method is used to update the active variables. At each iterative level, the search direction consists of three parts, one of which is a subspace truncated Newton direction, the other two are subspace gradient and modified gradient directions. The subspace truncated Newton direction is obtained by solving a sparse system of linear equations. The global convergence and quadratic convergence rate of the algorithm are proved and some numerical tests are given. 相似文献
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The two-sided rank-one (TR1) update method was introduced by Griewank and Walther (2002) for solving nonlinear equations. It generates dense approximations of the Jacobian and thus is not applicable to large-scale sparse problems. To overcome this difficulty, we propose sparse extensions of the TR1 update and give some convergence analysis. The numerical experiments show that some of our extensions are superior to the TR1 update method. Some convergence analysis is also presented. 相似文献
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交替方向法是求解可分离结构变分不等式问题的经典方法之一, 它将一个大型的变分不等式问题分解成若干个小规模的变分不等式问题进行迭代求解. 但每步迭代过程中求解的子问题仍然摆脱不了求解变分不等式子问题的瓶颈. 从数值计算上来说, 求解一个变分不等式并不是一件容易的事情.因此, 本文提出一种新的交替方向法, 每步迭代只需要求解一个变分不等式子问题和一个强单调的非线性方程组子问题. 相对变分不等式问题而言, 我们更容易、且有更多的有效算法求解一个非线性方程组问题. 在与经典的交替方向法相同的假设条件下, 我们证明了新算法的全局收敛性. 进一步的数值试验也验证了新算法的有效性. 相似文献
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本文提出了一个解不等式约束非线性规划问题有效方法.在这个方法中,考虑解一个等价Kuhn-Tucker条件的非线性方程组.这个方程组中NCP函数的使用消去了对应于不等式约束的Lagrange乘子的非负性.截断牛顿方法被用来解这个非线性方程组.为了保证全局收敛性,一个强健的损失函数被选为寻查函数,同时方法中插入修正最速下降方向.本文证明了方法的分Q-二阶收敛性,同时指出新方法可以有效地解稀疏大规模非线性规划问题。 相似文献
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无约束优化问题的对角稀疏拟牛顿法 总被引:3,自引:0,他引:3
对无约束优化问题提出了对角稀疏拟牛顿法,该算法采用了Armijo非精确线性搜索,并在每次迭代中利用对角矩阵近似拟牛顿法中的校正矩阵,使计算搜索方向的存贮量和工作量明显减少,为大型无约束优化问题的求解提供了新的思路.在通常的假设条件下,证明了算法的全局收敛性,线性收敛速度并分析了超线性收敛特征。数值实验表明算法比共轭梯度法有效,适于求解大型无约束优化问题. 相似文献
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Q. Ni 《计算数学(英文版)》1997,15(1):36-54
1.IntroductionInthispaperweconsiderthefollowingnonlinearprogrammingproblemminimizef(x)subjecttogj(x)2o,jEJ={1,...,m}.(1'1)Extensionstoproblemincludingalsoequalityconstraintswillbepossible.Thefunctionf:W-Rlandgj:Rn-R',jEJaretwicecontinuouslydifferentiable.Inpaxticular,weapplyQP-free(withoutquadraticprogrammingsubproblems),truncatedhybridmethodsforsolvingthelarge-scaJenonlinearprogrammingproblems,inwhichthenumberofvariablesandthenumberofconstraiotsin(1.1)aregreat.Wediscussthecase,wheresecon… 相似文献
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William La Cruz José Mario Martí nez Marcos Raydan. 《Mathematics of Computation》2006,75(255):1429-1448
A fully derivative-free spectral residual method for solving large-scale nonlinear systems of equations is presented. It uses in a systematic way the residual vector as a search direction, a spectral steplength that produces a nonmonotone process and a globalization strategy that allows for this nonmonotone behavior. The global convergence analysis of the combined scheme is presented. An extensive set of numerical experiments that indicate that the new combination is competitive and frequently better than well-known Newton-Krylov methods for large-scale problems is also presented.
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A new method of moving asymptotes for large-scale minimization subject to linear equality constraints is discussed.In this method,linear equality constraints are deleted with null space technique and the descending direction is obtained by solving a convex separable subproblem of moving asymptotes in each iteration. New rules for controlling the asymptotes parameters are designed and the global convergence of the method under some reasonable conditions is established and proved.The numerical results show that the new method may be capable of processing some large scale problems. 相似文献
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This study presents a novel adaptive trust-region method for solving symmetric nonlinear systems of equations. The new method uses a derivative-free quasi-Newton formula in place of the exact Jacobian. The global convergence and local quadratic convergence of the new method are established without the nondegeneracy assumption of the exact Jacobian. Using the compact limited memory BFGS, we adapt a version of the new method for solving large-scale problems and develop the dogleg scheme for solving the associated trust-region subproblems. The sufficient decrease condition for the adapted dogleg scheme is established. While the efficiency of the present trust-region approach can be improved by using adaptive radius techniques, utilizing the compact limited memory BFGS adjusts this approach to handle large-scale symmetric nonlinear systems of equations. Preliminary numerical results for both medium- and large-scale problems are reported. 相似文献
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我们考虑求解无约束优化问题1引言(?)f(x),(1)其中f:D(?)R~n→R为R~n上的二次连续可微函数,且f(x)的二阶Hesse阵H(x)稀疏、正定.为了求解问题(1),我们考虑下列Newton型方法x~(k 1)=x~k-(B~k)~(-1)▽f(x~k),k=0,1,…,(2)其中B~k是和Hesse阵H(x~k)具有相同稀疏性的近似.由于Hesse阵对称,我们假定B~k对称.为了具体说明给定矩阵B的稀疏性,我们使用M来定义指标对(i,j)的集合,其 相似文献
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为了改进求解大型稀疏线性互补问题模系多重网格方法的收敛速度和计算时间,本文采用加速模系超松弛(AMSOR)迭代方法作为光滑算子.局部傅里叶分析和数值结果表明此光滑算子能有效地改进模系多重网格方法的收敛因子、迭代次数和计算时间. 相似文献
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We present a modified damped Newton method for solving large sparse linear complementarity problems, which adopts a new strategy for determining the stepsize at each Newton iteration. The global convergence of the new method is proved when the system matrix is a nondegenerate matrix. We then apply the matrix splitting technique to this new method, deriving an inexact splitting method for the linear complementarity problems. The global convergence of the resulting inexact splitting method is proved, too. Numerical results show that the new methods are feasible and effective for solving the large sparse linear complementarity problems. 相似文献
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We present an algorithm, partitioning group correction (PGC) algorithm based on trust region and conjugate gradient method,
for large-scale sparse unconstrained optimization. In large sparse optimization, computing the whole Hessian matrix and solving
the Newton-like equations at each iteration can be considerably expensive when a trust region method is adopted. The method
depends on a symmetric consistent partition of the columns of the Hessian matrix and an inaccurate solution to the Newton-like
equations by conjugate gradient method. And we allow that the current direction exceeds the trust region bound if it is a
good descent direction. Besides, we studies a method dealing with some sparse matrices having a dense structure part. Some
good convergence properties are kept and we contrast the computational behavior of our method with that of other algorithms.
Our numerical tests show that the algorithm is promising and quite effective, and that its performance is comparable to or
better than that of other algorithms available. 相似文献
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In this article, unconstrained minimax problems are discussed, and a sequential quadratic programming (SQP) algorithm with a new nonmonotone linesearch is presented. At each iteration, a search direction of descent is obtained by solving a quadratic programming (QP). To circumvent the Maratos effect, a high-order correction direction is achieved by solving another QP and a new nonmonotone linesearch is performed. Under reasonable conditions, the global convergence and the rate of superlinear convergence are established. The results of numerical experiments are reported to show the effectiveness of the proposed algorithm. 相似文献
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A probabilistic version of the method of feasible directions (MFD) for solving nonlinear programming (NLP) problems of the type min{f(x): fj(x)0,j=1,2,…,m} is presented. Randomization is applied to modify the algorithm and a global convergence Theorem is used in the analysis of convergence. Some numerical experiments on problems with known solutions serve to compare this method with the traditional deterministic versions. 相似文献
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In this article, we propose a new smoothing inexact Newton algorithm for solving nonlinear complementarity problems (NCP) base on the smoothed Fischer-Burmeister function. In each iteration, the corresponding linear system is solved only approximately. The global convergence and local superlinear convergence are established without strict complementarity assumption at the NCP solution. Preliminary numerical results indicate that the method is effective for large-scale NCP. 相似文献