排序方式: 共有40条查询结果,搜索用时 421 毫秒
21.
Stefania Bellavia Maria Macconi Benedetta Morini 《Computational Optimization and Applications》2004,28(1):31-50
In this paper a Matlab solver for constrained nonlinear equations is presented. The code, called STRSCNE, is based on the affine scaling trust-region method STRN, recently proposed by the authors. The approach taken in implementing the key steps of the method is discussed. The structure and the usage of STRSCNE are described and its features and capabilities are illustrated by numerical experiments. The results of a comparison with high quality codes for nonlinear optimization are shown. 相似文献
22.
本文对一般非线性约束优化问题提出了一个信赖域算法,导出了等价的KKT条件.在试探步满足适当条件下,证明了算法的全局收敛性,并进行了数值试验. 相似文献
23.
This paper presents a trust-region method for solving the constrained nonlinear equation F(x) = 0, x , where R
n
is a nonempty and closed convex set, F is defined on the open set containing and is continuously differentiable. The iterates generated by the method are feasible. The method is globally and quadratically convergent under local error bounded assumption on F. The results obtained are extensions of the work of Yamashita Fukushima (Ref. 1) and Fan Yuan (Ref. 2) for unconstrained nonlinear equations. Numerical results show that the new algorithm works quite well. 相似文献
24.
Trust-region methods are powerful optimization methods. The conic model method is a new type of method with more information available at each iteration than standard quadratic-based methods. Can we combine their advantages to form a more powerful method for constrained optimization? In this paper we give a positive answer and present a conic trust-region algorithm for non-linearly constrained optimization problems. The trust-region subproblem of our method is to minimize a conic function subject to the linearized constraints and the trust region bound. The use of conic functions allows the model to interpolate function values and gradient values of the Lagrange function at both the current point and previous iterate point. Since conic functions are the extension of quadratic functions, they approximate general nonlinear functions better than quadratic functions. At the same time, the new algorithm possesses robust global properties. In this paper we establish the global convergence of the new algorithm under standard conditions. 相似文献
25.
提出了一类新的求解无约束最优化问题的新拟牛顿非单调信赖域算法.采用加权的r_k用以调整信赖域半径,在适当的条件下,证明了算法的全局收敛性.数值结果表明算法的有效性. 相似文献
26.
盛子宁 《高等学校计算数学学报》2009,31(1)
1 引言 简单界约束优化问题:minx∈(R)nf(x),l≤z≤u,其中f二阶可微,f∈((R)∪{-∞})n,u∈((R)∪{-∞})n(l相似文献
27.
Chen L. H. Deng N. Y. Zhang J. Z. 《Journal of Optimization Theory and Applications》1998,97(2):385-406
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. 相似文献
28.
In this paper, we propose and analyze a new conic trust-region algorithm for solving the unconstrained optimization problems. A new strategy is proposed to construct the conic model and the relevant conic trust-region subproblems are solved by an approximate solution method. This approximate solution method is not only easy to implement but also preserves the strong convergence properties of the exact solution methods. Under reasonable conditions, the locally linear and superlinear convergence of the proposed algorithm is established. The numerical experiments show that this algorithm is both feasible and efficient. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
29.
Thomas F. Coleman Jianguo Liu Wei Yuan 《Computational Optimization and Applications》2002,21(2):177-199
We present a new trust-region algorithm for solving nonlinear equality constrained optimization problems. Quadratic penalty functions are employed to obtain global convergence. At each iteration a local change of variables is performed to improve the ability of the algorithm to follow the constraint level set. Under certain assumptions we prove that this algorithm globally converges to a point satisfying the second-order necessary optimality conditions. Results of preliminary numerical experiments are reported. 相似文献
30.
一类拟牛顿非单调信赖域算法及其收敛性 总被引:2,自引:0,他引:2
本文提出了一类求解无约束最优化问题的非单调信赖域算法.将非单调Wolfe线搜索技术与信赖域算法相结合,使得新算-法不仅不需重解子问题,而且在每步迭代都满足拟牛顿方程同时保证目标函数的近似Hasse阵Bk的正定性.在适当的条件下,证明了此算法的全局收敛性.数值结果表明该算法的有效性. 相似文献