约束优化问题

非线性约束优化问题的一个修正Lagrangian算法

A Modified Lagrangian Algorithm for Solving Nonlinear Constrained Optimization Problems

本论文还将粒子群优化算法应用于实际的工程设计约束优化问题、多阈值图像分割问题以及SAR图像变化检测问题。

Afterwards , several PSO algorithms are applied to the real-world engineering design constrained optimization problems , multilevel thresholding for image segmentation and change detection for SAR images .

考虑解决无约束优化问题的PR共轭梯度算法。

The paper intents to solve the unrestraint optimum problem of PR conjugate gradient algorithms .

利用Fisher函数解约束优化问题的广义梯度投影算法

A Generalized Gradient Projection Algorithm with the Fisher Function for Solving the Constrained Optimization Problem

本文我们将探讨SA法在求解非线性约束优化问题中的应用。

In this paper , we will study SA algorithm in order to solve problem of non-linear constraint optimization .

在变分不等式与互补问题及平衡约束优化问题中也有信赖域算法可见，在最近兴起的filter方法中，信赖域方法也起着重要的作用。

For variational inequality problems and complementarity problems , one can also design the corresponding trust region algorithms . Moreover , it also play an important role in a recently developed filter method .

SWIFT法是非线性规划中一种用于求解约束优化问题的直接搜索法。

SWIFT is a direct search method in nonlinear programming ( NLP ), which is used to solve the constrained optimization problem .

本文基于Lagrange函数给出求解等式约束优化问题的一种新的迭代方法。

In this paper , a new iterative method for solving equality constrained optimization problem is presented based on the Lagrange function .

介绍粒子群优化（PSO）算法，并在此基础上利用带惯性权重因子的全局版PSO算法对结构模型修正和损伤检测等约束优化问题进行研究。

The Particle Swarm Optimization ( PSO ) algorithm is briefly introduced and then applied in structural model updating and structural damage detection .

求解凸集约束优化问题的共轭梯度的GLP投影算法

GLP conjugate gradient projection method for solving constraint problems

然后，采用增广Lagrangian方法把这个单目标约束优化问题转化成一个存在鞍点的二人零和博弈问题；

Second the augmented Lagrangian method is taken to transform the constrained optimization problem into a zero-sum game with the saddle-point solution .

BFGS算法是解无约束优化问题的公认的最有效的算法之一。

BFGS algorithm is one of the most effective methods in solving the non-constrained optimization problems .

郑权等在[1]&[3]中提出了一种求解无约束优化问题的均值算法，若假设目标函数f（x）是连续的，还讨论了均值算法的收敛性。

Zheng Quan etc present a mean method for solving unconstrained optimization problems in [ 1 ] - [ 3 ] , if the objective function is continuous , prove convergence of the mean method .

依据罚函数及动态处罚法设计增广Lagrange乘子函数，获得新的神经网络模型解决约束优化问题。

A novel neural network , of which is applied to universal nonlinear constrained optimization , is proposed based dynamical penalty function method and general Lagrange multiply one .

提供非单调内点回代技术的信赖域投影Hessian算法解线性约束优化问题。

We propose a new trust region projected Hessian algorithm with nonmonotonic backtracking interior point technique for linear constrained optimization .

PR共轭梯度法是求解大型无约束优化问题的有效算法之一，但是算法的全局收敛性在理论上一直没有得到解决。

PR conjugate gradient method is one of the efficient methods for solving large scale unconstrained optimization problems , however , its global convergence has not been solved for a long time .

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。

Sequential Unconstrained Minimization Techniques ( SUMT ) are most common and comparatively successful method in constrained optimization .

本文主要研究求解约束优化问题的Filter型算法。论文共分五部分。在第一章中我们首先介绍了优化问题的模型、基本求解思路以及算法的收敛性和收敛速度等一系列概念。

In this paper , we study the Filter-type algorithms for constrained optimization problems and the paper is divided into five parts . First , we introduce the model , the basic method of constrained optimization problems and some concepts about the convergence of algorithms .

这样原问题就变成块可分的等价问题，可以直接用块可分约束优化问题的PVD算法进行求解。本文给出了混合整数非线性约束优化问题的PVD算法及其全局收敛性证明。

So the mix-integer nonlinear optimization problem becomes separable constrained optimization problem , which can be solved by PVD algorithm of separable constrained optimization problem .

用Hooke-Jeeves提出的模式搜索法来求解有约束优化问题，从而克服了传统的Newton-Raphson法稳定性差与难于处理有约束条件之弱点。

The direct search method used to solve the constrained optimization problem is more flexible and stable than the Newton-Raphson method .

将最速下降法与Newton法有机地结合起来，构造了无约束优化问题的一种组合迭代算法，并证明了算法的全局收敛性.一类组合迭代过程的收敛性与误差估计

A hybrid iterative algorithm for unconstrained optimization problems is formulated by means of combining organically the steepest decent method and Newton method . ON THE CONVERGENCE AND ERROR ANALYSIS OF A CLASS OF ITERATION PROCEDURES GENERATED BY COMPOSITION

结合新的线搜索规则，本文设计了一类求解无约束优化问题的具有充分下降性的谱PRP共轭梯度算法。

On the basis of this new line search , a new spectral PRP conjugate gradient algorithm is developed for solving unconstrained optimization problems , where the search direction is sufficiently descent .

该文将微粒群算法（PSO）应用于非线性约束优化问题的求解，提出了一种求解非线性约束优化问题的新算法，数值试验表明该算法具有很强的全局寻优能力。

This paper use particle swarm algorithm ( PSO ) to solve Nonlinear Constrained Optimization Problems , a new algorithm based on particle swarm algorithm is given and numerical experiences show that the new algorithm has powerful ability of global searching .

通过对标准微粒群算法（PSO）改进，采用动态罚函数的方法，提出了一种求解非线性约束优化问题的新算法。

This Paper presents a new evolutionary algorithm for solving nonlinear constrained optimization problems based on particle swarm optimizer ( PSO ) . Dynamic penalty function is adopted in this algorithm to transform the constrained optimization problems into unconstrained optimization problems .

智能组卷是CBT的基础，组卷中关键是解决生成满足教学和教师要求的试题，即约束优化问题。

Computer Test Construction is the basis of CBT , its key problem is to construct the test paper which satisfies the teaching and meets the teachers ' demands , that means constraint optimization problems .

由于小波域HMT模型准确刻画了自然图像小波变换的统计特性，该文算法以此作为自然图像的先验模型，将图像复原问题转化为一个约束优化问题并用最速下降法对其进行求解。

The proposed algorithm specifies the prior distribution of real world images through wavelet domain HMT model and converts the restoration problem to an constrained optimization task which can be solved with the steepest descend method .

提出一个求解LC1无约束优化问题的信赖域算法，在较弱条件下证明了全局收敛性和超线性收敛性。

A trust region method for LC ~ 1 unconstrained problems was presented and under mild conditions we proved its global and superlinear convergene .

本文通过引入松弛变量和Fischer函数把带有不等式约束优化问题的K-T条件转化为一个等价的非线性系统，并引入一参数μ，从而提出了一种新的光滑牛顿法。

In this paper , the K-T conditions of inequality constrained optimization is transformed to a equi-valent nonlinear system by adding slack variables and using Fischer function , and a new smoothing Newton method is proposed , where a parameter μ is introduced .

针对高维复杂约束优化问题，提出了一种基于平滑技术和一维搜索的粒子群算法（NPSO）。

A novel particle swarm optimization ( NPSO ) based on the smooth scheme and line search is proposed for solving complex constrained optimization problems .

对求解无约束优化问题提出了一类新的三项共轭梯度求解算法，在去掉迭代点列{xk}有界和Armijo步长搜索下，讨论了算法的全局收敛性。

A new three-term conjugate gradient method is proposed for solving the unconstrained optimization problem . Global convergence is discussed with Armijo step size rule and without assuming that the sequence { x_k } of iterates is bounded .