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。
A trust-region methods which were replaced by line search methods were adopted to assure the global .
为了保证算法的总体收敛性，应用信赖域算法代替一维搜索，确定下一个迭代点。
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。
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。
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。
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。
Trust region method is a kind of efficient methods to solve the general unconstrained optimization and its special situation, the nonlinear least squares problems.
对于一般的无约束最优化问题及其特殊情况非线性最小二乘问题而言，信赖域方法是一种有效的方法。
Trust region method is a kind of efficient and robust method to solve general unconstrained optimization.
对于一般的无约束优化问题，信赖域方法是一种比较有效的方法。
Numerical example is presented to compare with pure trust region method and combining method for calculation.
通过计算实例，比较了纯信赖域算法与组合算法的计算工作量。
Approximation management framework is a model management framework that based on trust region method, and it aims to construct an optimization method that based on different models.
变可信度模型管理结构是在信赖域方法的基础上，为建立基于不同分析模型的优化方法提出的模型管理框架。
This paper is to study the convergence properties of the gradient projection method with trust region strategy for constrained optimization.
本文使用信赖域策略结合投影梯度算法来解约束优化问题，并给出算法及其收敛性。
Trust region interior point method can settle the problem of adjusting step sizes on successive linear programming well.
信赖域内点法可以很好地解决逐线性规划方法中的步长调整问题。
Numerical results show that we choose a suitable initial adaptive trust region radius at each iteration so as to reduce the number of iterations, function and gradient evaluations.
数值试验结果表明，我们改进后的信赖域半径使算法在迭代过程中十分有效，不但减少了迭代次数还减少了函数和梯度的赋值。
In this paper, we propose a new class of trust region methods for nonlinear optimization problems.
本文提出一类新的解无约束最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。
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。
The trust region method is one of the most valid ways to study optimization problems.
信赖域方法是研究最优化问题的有效方法之一。
A new nonmonotonic trust region method is given in this paper. And its global convergence and superlinear convergence are proved. Numerical results are given.
给出一种新的非单调信赖域方法，证明了算法的全局收敛性和超线性收敛性，最后给出了数值结果。
At the second part, nonmonotonic trust region method for unconstrained optimization is studied.
第二部分主要研究无约束最优化问题非单调信赖域法。
In this paper, a trust region method with new conic model for linearly constrained optimization problems is proposed.
本文提出了一个解线性等式约束优化问题的新锥模型信赖域方法。
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。
Trust region methods are efficient for solving unconstraint optimization problems.
信赖域算法是求解最优化问题的一类有效算法。
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。
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 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。
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 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。
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。
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。
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