The idea of trust region algorithm was employed to approach the closest critical point.
基于信赖域方法的思想迭代逼近最近电压稳定临界点。
In chapter 3, we present a nonmonotonic trust region algorithm based on the conic model.
第三章，我们提出了一类基于锥模型的非单调信赖域算法。
In this paper, we develop a trust region algorithm for convex constrained optimization problems.
本文我们考虑求解凸约束优化问题的信赖域方法。
Both line search and trust region algorithm are well-accepted methods in the optimization to assure global convergence.
线性搜索方法和信赖域方法是保证最优化问题的整体收敛性的两种基本策略。
A nonmonotonic trust region algorithm with line search for unconstrained optimization problems is presented in this paper.
给出无约束最优化的一类带线搜索的非单调信赖域算法。
We discuss non-monotonic trust region algorithm for unconstrained nonlinear optimization problems in view of Trust Region Model mainly.
然后从信赖域子问题的角度出发，对无约束优化问题提出了一个改进的非单调信赖域算法。
We propose a new trust region algorithm for special linear inequality constrained optimization problems with nonnegative bound constraints.
对一类带有非负边界约束的线性不等式约束优化问题进行了研究，提出了一种新的信赖域算法。
In this paper, we propose a new trust region algorithm for solving a class of composite nonsmooth optimization subject to convex constraints.
提出了求解一类带一般凸约束的复合非光滑优化的信赖域算法。
We apply the popular trust region algorithm and truncated conjugate gradient algorithm with trust region skills to solve trust region subproblems.
应用目前流行的信赖域算法，并用带有信赖域技巧的截断共扼梯度法来解信赖域子问题。
In this paper, a trust region algorithm for general nonlinear equality constrained optimization problems, is presented. The solution of their subproblems is easy.
对一般非线性等式约束最优化问题提出了一种信赖域算法，其子问题较易求解。
Since the homogeneous model can approximate the objective function better than the quadratic model, the new algorithm is superior to the classical trust region algorithm.
由于该模型比二次模型更近似目标函数，故新算法优于传统的信赖域算法。
We present an affine scaling trust region algorithm with interior back - tracking and subspace techniques for nonlinear optimizations subject to linear inequality constraints.
使用仿射变换内点回代技术的信赖域子空间算法解线性不等式约束的非线性优化问题。
This paper presents a trust region algorithm based upon the homogeneous model. The traditional trust region algorithm based on the quadratic model is one of its special cases.
提出一种基于齐次模型的信赖域算法，传统的基于二次模型的信赖域算法只是它的一个特例。
In order to overcome the disturbance of noises, a robust identification method of water quality model parameters namely trust region algorithm based on M-estimation is proposed.
为了克服随机噪声对河流水质模型参数估计的干扰，提出了一种水质模型参数的鲁棒估计方法，即基于M -估计的信赖域算法。
In recent years, the conic model for the study of trust region algorithm has aroused wide spread concern, made up for the deficiencies of quadratic model trust region algorithm.
近年来，锥模型信赖域算法的研究引起了专家们的普遍关注，弥补了二次模型信赖域算法的缺陷。
This paper presents a trust region algorithm for solving the constrained interpolation and smoothing problems such as convex interpolation, convex smoothing and shape-preserving interpolation.
针对凸插值、凸光顺和保形插值等带约束条件的插值和光顺问题，提出一种信赖域方法。
In this paper, we propose a projected trust-region algorithm for solving bound-constrained smooth systems of equations.
本文提供了在没有非奇异假设的条件下，求解有界约束半光滑方程组的投影信赖域算法。
The strong convergence of the algorithm under a general choice for radius of trust region is proved.
在一个很广泛的信赖域半径选择规则下，证明了算法的强收敛性。
Aiming at the shortcomings of trust region method, we proposed an algorithm using negative curvature direction as its searching direction. The convergence of the algorithm was given.
针对模型信赖域方法中搜索方向存在的不足，提出了按负曲率方向进行搜索的模型信赖域算法，并证明了算法的收敛性。
This paper proposes a trust-region-type succesive linear algorithm with self-adjusted penalty parameter for nonlinear constrained optimization.
对于非线性约束最优化，提出了一个自动调节罚因子的信赖域类型的逐次线性算法。
Trust region type algorithm possesses very good theoretical properties.
结合信赖域技术，算法具有良好的理论性态。
Numerical results show that the present algorithm is efficient and reliable. The last chapter, we present a modified filter trust region method for bound constrained problems.
第六章，由第五章求解无约束问题的多维滤子信赖域修正算法出发，将其推广到界约束乃至凸约束的优化问题。
This paper presents a novel algorithm for the OPF problem based on a trust region method.
文中基于信赖域的思想提出了求解opf的新算法。
This paper puts forward the adaptive trust-region algorithm based on the conic model for unconstrained optimization.
无 约束优化 问题提出了基于锥模型的自适应信赖域算法。
The paper proposes a nonmonotonic BFGS-trust-region algorithm for unconstrained optimization.
给出了一个解无约束最优化问题的非单调的新的BFGS校正的信赖域算法。
The global convergence results are given for the nonmonotonic trust region technique. Furthermore, the proposed algorithm is superlinearly convergent under a certain growth condition.
证明了此方法的全局收敛性，并给出了它在一定条件下的超线性收敛的结果。
The global convergence results are given for the nonmonotonic trust region technique. Furthermore, the proposed algorithm is superlinearly convergent under a certain growth condition.
证明了此方法的全局收敛性，并给出了它在一定条件下的超线性收敛的结果。
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