Description: 给出变量的上下边界、初值和代价函数，能够搜索代价函数最小值时的变量取值。属于带约束的优化算法，可以用来求算非线性方程组。-STRSCNE is a Matlab code for constrained nonlinear systems of equations
F(x)=0 l<=x<=u
where F: R^n--> R^n, l and u are vectors of dimension n. Non-existent lower and upper bounds, i.e.
entries of l and u equal to minus o plus infinity, are allowed.
The algorithm is a globally convergent procedure that combines Newton method and an elliptical trust-region approach. The elliptical trust-region is defined employing a scaling diagonal matrix D
and the trust-region subproblem is approximately solved by the dogleg method. Only strictly feasible iterates are generated.
Various input/output options are provided, and we refer to the code itself for further documentation.
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Author:muxihan |
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Description: matlab最优化程序包括
无约束一维极值问题
进退法 黄金分割法 斐波那契法 牛顿法基本牛顿法 全局牛顿法 割线法 抛物线法 三次插值法 可接受搜索法
Goidstein法 Wolfe.Powell法
单纯形搜索法 Powell法 最速下降法
共轭梯度法 牛顿法 修正牛顿法
拟牛顿法 信赖域法 显式最速下降法，
Rosen梯度投影法
罚函数法 外点罚函数法 內点罚函数法
混合罚函数法 乘子法
G－N法 修正G－N法 L－M法
线性规划 单纯形法 修正单纯形法
大M法 变量有界单纯形法
整数规划 割平面法 分支定界法
0-1规划 二次规划
拉格朗曰法 起作用集算法
路径跟踪法
粒子群优化算法 基本粒子群算法 带压缩因子的粒子群算法 权重改进的粒子群算法
线性递减权重法 自适应权重法
随机权重法 变学习因子的粒子群算法
同步变化的学习因子
异步变化的学习因子 二阶粒子群算法
二阶振荡粒子群算法
-matlab optimization process includes
Non-binding one-dimensional extremum problems
Advance and retreat method Golden Section Fibonacci method of basic Newton s method Newton s method Newton s Law of the global secant method parabola method acceptable to the three interpolation search method
Goidstein France Wolfe.Powell France
Simplex search method Powell steepest descent method
Conjugate gradient method Newton s method Newton s method to amend
Quasi-Newton Method trust region method explicitly steepest descent method,
Rosen gradient projection method
Penalty function method outside the penalty function method within the penalty function method
Mixed penalty function multiplier method
G-N was amended in G-N method L-M method
Of linear programming simplex method, revised simplex method
Big M method variables bounded simplex method,
Cutting Plane Method integer programming branch and bound method
0-1 programming quadratic programming
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Author:百位过 |
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Description: Numerical Optimization-Every year optimization algorithms are being called on to handle problems that are much larger and complex than in the past. Accordingly, the book emphasizes large- scale optimization techniques, such as interior-point methods, inexact Newton methods, limited-memory methods, and the role of partially separable functions and automatic differentiation. It treats important topics such as trust-region methods and sequential quadratic programming more thoroughly than existing texts, and includes comprehensive discussion of such “core curriculum” topics as constrained optimization theory, Newton and quasi-Newton methods, nonlinear least squares and nonlinear equations, the simplex method, and penalty and barrier methods for nonlinear programming. Platform: |
Size: 5659648 |
Author:Nu |
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Description: LM算法
老外写的The Levenberg-Marquardt (LM) algorithm is the most widely used optimization algorithm. It
outperforms simple gradient descent and other conjugate gradient methods in a wide variety of
problems. This document aims to provide an intuitive explanation for this algorithm. The LM
algorithm is fi rst shown to be a blend of vanilla gradient descent and Gauss-Newton iteration.
Subsequently, another perspective on the algorithm is provided by considering it as a trust-region
method-The Levenberg-Marquardt (LM) algorithm is the most widely used optimization algorithm. It
outperforms simple gradient descent and other conjugate gradient methods in a wide variety of
problems. This document aims to provide an intuitive explanation for this algorithm. The LM
algorithm is fi rst shown to be a blend of vanilla gradient descent and Gauss-Newton iteration.
Subsequently, another perspective on the algorithm is provided by considering it as a trust-region
method Platform: |
Size: 31744 |
Author:TANG |
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Description: matlab最优化程序包括 无约束一维极值问题 进退法 黄金分割法 斐波那契法 牛顿法基本牛顿法 全局牛顿法 割线法 抛物线法 三次插值法 可接受搜索法 Goidstein法 Wolfe.Powell法 单纯形搜索法 Powell法 最速下降法 共轭梯度法 牛顿法 修正牛顿法 拟牛顿法 信赖域法 显式最速下降法-matlab optimization program includes one-dimensional extremum problem without constraint advance and retreat method Fafei Bo Fibonacci golden section method the basic Newton method, global Newton method Newton secant parabola method acceptable to the three interpolation methods Wolfe.Powell search method Goidstein simplex method Searching Powell steepest descent method conjugate gradient method modified Newton method Newton Newton trust region method to be explicitly steepest descent method Platform: |
Size: 780288 |
Author:林小博 |
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Description: CO is an applications module written in the GAUSS programming language. It solves the Nonlinear Programming problem, subject to general constraints on the parameters - linear or nonlinear, equality or inequality, using the Sequential Quadratic Programming method in combination with several descent methods selectable by the user - Newton-Raphson, quasi-Newton (BFGS and DFP), and scaled quasi-Newton. There are also several selectable line search methods. A Trust Region method is also available which prevents saddle point solutions. Gradients can be user-provided or numerically calculated. -CO is an applications module written in the GAUSS programming language. It solves the Nonlinear Programming problem, subject to general constraints on the parameters- linear or nonlinear, equality or inequality, using the Sequential Quadratic Programming method in combination with several descent methods selectable by the user- Newton-Raphson, quasi-Newton (BFGS and DFP), and scaled quasi-Newton. There are also several selectable line search methods. A Trust Region method is also available which prevents saddle point solutions. Gradients can be user-provided or numerically calculated. Platform: |
Size: 37888 |
Author:王知章 |
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Description: 基于matlab编写了SQP法，乘子法，共轭梯度法，拟牛顿法，信赖域法，最速下降法与牛顿法的最新程序，功能很强大，可供编程参考。-Based on the preparation of MATLAB SQP, multiplier method, conjugate gradient method, quasi-Newton method, trust region method, steepest descent method with the Newton-Raphson method the latest procedures, functions very powerful, can be used for programming reference. Platform: |
Size: 25600 |
Author:丁长涛 |
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Description: matlab程序非线性优化设计方法时下流行的关于非线性规划的源程序,包括SQP方法、乘子法程序、二次规划、非线性最小二乘法、共轭梯度法、拟牛顿法、线搜索技术、信赖域方法、最速下降法与牛顿法等-matlab program nonlinear optimization design method popular on nonlinear programming source code, including the SQP method, the multiplier method procedures, quadratic programming, nonlinear least squares method, the conjugate gradient method, quasi-Newton method, the linesearch technology, trust region methods, the steepest descent method and Newton method Platform: |
Size: 34816 |
Author:朱志远 |
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Description: 无约束多维极值问题，包含
用模式搜索法求解多维函数的极值
用Rosenbrock法求解多维函数的极值
用单纯形搜索法求解多维函数的极值
用Powell法求解多维函数的极值
用最速下降法求解多维函数的极值
用共轭梯度法求解多维函数的极
用牛顿法求解多维函数的极值
用修正牛顿法求解多维函数的极值
用DFP法求解多维函数的极值
用BFGS法求解多维函数的极值
用信赖域法求解多维函数的极值
用显式最速下降法求正定二次函数的极值
-Unconstrained multidimensional extremal problem contains the pattern search method for solving the multi-dimensional function extremum with Rosenbrock method for solving multidimensional function extremum simplex search method to solve the multi-dimensional function extremum Powell method for solving multidimensional function extremum with the steepest descent pole with Newton' s method for solving multidimensional function method for solving the multi-dimensional function extremum with conjugate gradient method to solve the multi-dimensional function extremum modified Newton method for solving multidimensional function extremum with DFP method to solve the multi-dimensional function extremum BFGS method for solving multidimensional seeking positive definite quadratic function extremum function extremum trust region method for solving multidimensional function extremum with explicit steepest descent method Platform: |
Size: 6144 |
Author:张然 |
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Description: 光滑牛顿法求解信赖域子问题，使用近似Hesse矩阵正定情形，并给出该方法信赖域方法的matlab程序-Smoothing Newton method for solving the trust region subproblem approximate Hesse matrix positive definite situation, and given that the method of trust region methods matlab program Platform: |
Size: 2048 |
Author:粥 |
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Description: 本书系统的介绍了非线性优化的理论与方法及其matlab程序设计，本书的主要内容包括:最速下降法与牛顿法；共轭梯度法；拟牛顿法；信赖域法；线性最小二乘问题的解法；序列二次规划法；以及matlab最有工具。
-This book introduces the system of nonlinear optimization theory and methods and matlab programming, the main contents of this book include: the steepest descent method and Newton method conjugate gradient method quasi-Newton method trust region method linear least squares Problem Solution sequential quadratic programming and most matlab tool. Platform: |
Size: 1895424 |
Author:明康中锦 |
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Description: 《最优化方法及其Matlab程序设计》较系统地介绍了非线性最优化问题的基本理论和算法，以及主要算法的Matlab程序设计，主要内容包括（精确或非精确）线搜索技术、最速下降法与（修正）牛顿法、共轭梯度法、拟牛顿法、信赖域方法、非线性最小二乘问题的解法、约束优化问题的最优性条件、罚函数法、可行方向法、二次规划问题的解法、序列二次规划法等。-" Optimization Methods and Matlab programming," a more systematic introduction to nonlinear optimization problem of the basic theory and algorithms, as well as the main algorithm Matlab programming, the main contents include (precise or exact) line search technique, the steepest descent method and (amended) Newton method, conjugate gradient method, quasi-Newton method, trust region method, nonlinear least squares problem solution, constrained optimization problems optimality conditions penalty function method, feasible direction method, quadratic programming problem The solution, sequential quadratic programming method. Platform: |
Size: 1792000 |
Author:赵雪伟 |
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Description: 本书较为系统地介绍了非线性最优化问题的基本理论和算法及主要算法的matlab程序设计，主要内容包括线搜索技术，最速下降法与牛顿法，共轭梯度法，拟牛顿法，信赖域方法，非线性最小二乘问题的解法，约束优化问题的最优性条件，罚函数法，可行方向法，二次规划问题的解法，序列二次规划法等。-This book systematically introduces the nonlinear optimization problem of the basic theory and algorithms and key algorithm matlab program design, including line search technique, the steepest descent method and Newton' s method, conjugate gradient method, quasi-Newton method, trust region method, nonlinear least squares problem solution, constrained optimization problems optimality conditions penalty function method, feasible direction method, the solution of quadratic programming problems, sequential quadratic programming method. Platform: |
Size: 7461888 |
Author:whucs |
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Description: 功能：牛顿型信赖域方法求解无约束优化问题min f(x)
输入 x0是初始迭代点
输出：xk是近似极小点，val是近似极小值，k是迭代次数- function: Newton type trust region method for solving unconstrained optimization problem min f (x)
input The xo is the initial iteration point
output: xk is approximate minimum point, val is approximate minimum, k is the number of iterations Platform: |
Size: 3072 |
Author:苗小楠 |
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Search - trust region Newton