共查询到20条相似文献,搜索用时 140 毫秒
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针对二次规划逆问题,将其表达为带有互补约束的锥约束优化问题.借助于对偶理论,将问题转化为变量更少的线性互补约束非光滑优化问题.通过扰动的方法求解转化后的问题并证明了收敛性.采用非精确牛顿法求解扰动问题,给出了算法的全局收敛性与局部二阶收敛速度.最后通过数值实验验证了该算法的可行性. 相似文献
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本文设计了一个新的求解等式约束非凸优化问题的修正牛顿算法.利用修正的拉格朗日函数,通过求解线性方程组获得搜索方向,利用价值函数的线性近似模型确定步长.在没有非奇异性假设的条件下,证明了算法的全局收敛性.数值结果表明,算法是有效的. 相似文献
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对约束优化问题给出了一类光滑罚算法.它是基于一类光滑逼近精确罚函数 l_p(p\in(0,1]) 的光滑函数 L_p 而提出的.在非常弱的条件下, 建立了算法的一个摄动定理, 导出了算法的全局收敛性.特别地, 在广义Mangasarian-Fromovitz约束规范假设下, 证明了当 p=1 时, 算法经过有限步迭代后, 所有迭代点都是原问题的可行解; p\in(0,1) 时,算法经过有限迭代后, 所有迭代点都是原问题可行解集的内点. 相似文献
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牛潇萌 《数学的实践与认识》2016,(6):240-247
给出求解p_0函数非线性互补问题光滑化拟牛顿算法,在p_0函数非线性互补问题有非空有界解集且F'是Lipschitz连续的条件下,证明了算法的全局收敛性.全局收敛性的主要特征是不需要提前假设水平集是有界的. 相似文献
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对不等式约束优化问题提出了一个低阶精确罚函数的光滑化算法. 首先给出了光滑罚问题、非光滑罚问题及原问题的目标函数值之间的误差估计,进而在弱的假
设之下证明了光滑罚问题的全局最优解是原问题的近似全局最优解. 最后给出了一个基于光滑罚函数的求解原问题的算法,证明了算法的收敛性,并给出数值算例说明算法的可行性. 相似文献
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提出了求解非线性互补问题的一个逐次逼近拟牛顿算法。在适当的假设下,证明了该算法的全局收敛性和局部超线性收敛性。 相似文献
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Zheng Peng Donghua Wu Quan Zheng 《Journal of Optimization Theory and Applications》2013,156(2):493-523
In this paper, we propose a new method, namely the level-value estimation method, for finding global minimizer of continuous optimization problem. For this purpose, we define the variance function and the mean deviation function, both depend on a level value of the objective function to be minimized. These functions have some good properties when Newton’s method is used to solve a variance equation resulting by setting the variance function to zero. We prove that the largest root of the variance equation equals the global minimal value of the corresponding optimization problem. We also propose an implementable algorithm of the level-value estimation method where importance sampling is used to calculate integrals of the variance function and the mean deviation function. The main idea of the cross-entropy method is used to update the parameters of sample distribution at each iteration. The implementable level-value estimation method has been verified to satisfy the convergent conditions of the inexact Newton method for solving a single variable nonlinear equation. Thus, convergence is guaranteed. The numerical results indicate that the proposed method is applicable and efficient in solving global optimization problems. 相似文献
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E. J. Beltrami 《Journal of Optimization Theory and Applications》1985,45(3):477-480
Implementation of the penalty function method for constrained optimization poses numerical difficulties as the penalty parameter increases. To offset this problem, one often resorts to Newton's method. In this note, working in the context of the penalty function method, we establish an intimate connection between the second-order updating formulas which result from Newton's method on the primal problem and Newton's method on the dual problem.The author wishes to thank Professor R. A. Tapia for his careful review of this note. He has contributed significantly to its content through several crucial observations. 相似文献
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Quan Zheng Rongxia Bai Zhongli Liu 《Journal of Computational and Applied Mathematics》2008,220(1-2):480-489
In this paper, we discuss two variants of Newton's method without using any second derivative for solving nonlinear equations. By using the majorant function and confirming the majorant sequences, we obtain the cubic semilocal convergence and the error estimation in the Kantorovich-type theorems. The numerical examples are presented to support the usefulness and significance. 相似文献
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Adler Roy L.; Dedieu Jean-Pierre; Margulies Joseph Y.; Martens Marco; Shub Mike 《IMA Journal of Numerical Analysis》2002,22(3):359-390
To study a geometric model of the human spine we are led tofinding a constrained minimum of a real valued function definedon a product of special orthogonal groups. To take advantgeof its Lie group structure we consider Newton's method on thismanifold. Comparisons between measured spines and computed spinesshow the pertinence of this approach. 相似文献
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本文研究非线性互补问题(NCP)的求解算法,先将NCP转化为约束全局优化问题(CGOP),然后直接移植求解问题(CGOP)的水平值估计算法^[4,5]来求解问题(NCP).文章证明了算法对于NCP是收敛的,数值实验说明了算法的有效性. 相似文献
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结合遗传算法全局高效搜索和牛顿法局部细致搜索的优势,充分利用一种算法的优点弥补另一种算法的不足,进而引入一种基于遗传算法和牛顿法的联合算法,并将联合算法应用于反演地表发射率的函数关系中.结果表明,联合算法中由遗传算法提供的初始值使得牛顿法下降的速度快,且很快趋于稳定,达到精度要求;而由任意初始值提供给牛顿法,目标函数下降到一定阶段后反而有所回升,然后才保持稳定,且经和联合算法迭代相同的次数后,目标函数的值仍然非常大,远远达不到要求.因此,从可行性、计算效率上看,联合算法均优于单纯的牛顿法,是一种性能稳定,计算高效的下降方法. 相似文献
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Liang Fang Guoping He Zhongyong Hu 《Journal of Computational and Applied Mathematics》2008,220(1-2):409-412
Under weak conditions, we present an iteration formula to improve Newton's method for solving nonlinear equations. The method is free from second derivatives, permitting f′(x)=0 in some points and per iteration it requires two evaluations of the given function and one evaluation of its derivative. Analysis of convergence demonstrates that the new method is cubically convergent. Some numerical examples illustrate that the algorithm is more efficient and performs better than classical Newton's method. 相似文献
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Using the forms of Newton iterative function, the iterative function of Newton's method to handle the problem of multiple roots and the Halley iterative function, we give a class of iterative formulae for solving equations in one variable in this paper and show that their convergence order is at least quadratic. At last we employ our methods to solve some non-linear equations and compare them with Newton's method and Halley's method. Numerical results show that our iteration schemes are convergent if we choose two suitable parametric functions λ(x) and μ(x). Therefore, our iteration schemes are feasible and effective. 相似文献