In this paper, a kind of general constrained optimization problem is discussed.
在本文中，我们讨论的是一般约束优化的问题。
In this paper, we consider the nonlinear inequality constrained optimization problems.
在本文中，我们考虑非线性不等式约束优化问题。
Automatic Test Paper is a combination of multi-objective constrained optimization problem.
智能组卷是一个多约束目标的组合优化问题。
To solve complex constrained optimization problems, we propose a new immune-genetic algorithm.
提出一种新的求解复杂约束优化问题的免疫遗传算法。
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。
A subspace truncated-Newton algorithm for large-scale bound constrained optimization is proposed.
给出了大规模界约束优化的一个子空间截断牛顿法。
We present an algorithm for the solution of general inequality constrained optimization problems.
我们提出一个一般不等式约束优化问题的求解算法。
In this paper, we consider an affine-scaling algorithm for the bound constrained optimization problem.
本文我们考虑求解边界约束优化问题的一个仿射尺度算法。
BFGS algorithm is one of the most effective methods in solving the non-constrained optimization problems.
BFGS算法是解无约束优化问题的公认的最有效的算法之一。
Therefore, its KKT conditions are different from those of the general equality constrained optimization problem.
转化后的问题要求其乘子是非负的，故其KKT条件与一般的等式约束优化问题不同。
Layout optimization is an NP-hard problem. It also belongs to complex nonlinear constrained optimization problem.
布局优化是NP难问题，也是复杂的非线性约束优化问题。
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。
The method is based on the regularization technique, solving the constrained optimization by proposed iteration steps.
该方法利用正则化技术，通过迭代运算解求重建影像的最优解。
The method of feasible directions (MFD for short) is an important method for solving nonlin-early constrained optimization.
可行方向法（简称为MFD）是用于求解非线性约束最优化重要的方法之一。
The equations of nonlinearly constrained optimization are presented for the evaluation of the minimal circumscribed sphere.
本文把最小外接球的评定问题表述为非线性约束最优化问题，并采用有效约束技术求得精确的最优解。
In this paper, a modified sequential quadratic program (SQP) for inequality constrained optimization problems is presented.
本文对不等式优化问题提出了一个修正的序列二次规划算法(SQP)。
A method for solving minimax problem is presented, which also can be used to solve linear or constrained optimization problems.
提出了一类解极小极大问题的熵函数法，这种方法也可用来解线性或约束优化问题。
Based on the orthogonality of rotation matrix, a constrained optimization approach is proposed to estimate the rotation matrix.
本文利用旋转矩阵的正交性，提出了进一步改善原旋转矩阵估计的约束优化方法。
Starting with the constrained optimization method, an algorithm for the even distribution of the machining allowance is developed.
从约束优化方法入手，提出了复杂等距型面加工余量均布优化算法。
Sequential Unconstrained Minimization Techniques (SUMT) are most common and comparatively successful method in constrained optimization.
罚函数法(SUMT)是处理约束优化问题时最常用、也是较为成功的一种方法。
In this paper, the constrained optimization problem is discussed to arrive at a general perturbed gradient projection method for solution.
讨论带不等式和等式约束优化问题，提出了求解非线性规划问题的广义摄动梯度投影算法。
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。
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。
Image matching belongs to constrained optimization problems. Whether the system would converge to the global optimum is still an open problem.
图像匹配是一种约束最优化问题，系统是否收敛于全局最优值一直尚未解决。
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。
The Chaotic neural network model can be used to solve many multi-dimensioned, discrete, non-convex, nonlinear constrained optimization problems.
基于混沌神经网络模型可以有效地解决高维、离散、非凸的非线性约束优化问题。
Nondifferentiable exact penalty functions are used to transform a constrained optimization problem into a single unconstrained optimization problem.
借助不可微精确罚函数把约束问题转化为单个无约束问题来处理。
The aim of the dissertation is to study second order derivatives based differential equation approaches to nonconvex constrained optimization problems.
本文旨在研究求解非凸约束优化问题的基于二阶导数的微分方程方法。
At the mean time, the penalty function was improved by transmuting the inequality constrained optimization problem into single target optimization one.
同时为了将不等式约束优化问题转化为单目标优化问题，对惩罚函数法进行了改进。
This algorithm joint the constrained optimization algorithm and subspace algorithm, can improve the system performance in strong interfere environment.
改进的多用户检测算法将子空间算法和约束优化算法结合起来，在强干扰信道中能有效提高系统性能。
应用推荐