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- Armijo line search method Rosenbrock Function Projection boundry condition-Armijo line search method Rosenbrock Function Projection boundry condition
cpp
- 最速下降/牛顿法 armijo线性搜索 比较 F(x)=x2+2x2-ln(x1x2-1) 迭代次数、步长 精度ε=0.1 σ1=0.4 ρ=0.5-Steepest descent/Newton method armijo linear search compare F (x) = x2+ 2x2-ln (x1x2-1) iterations, step length Precision ε = 0.1 σ1 = 0.4 ρ = 0.5
frcg
- FR共轭梯度法求解无约束优化问题，其中一维搜索用Armijo搜索。-Fletcher-Reeves method for optimization
CG_optimal
- 共轭梯度法求解无约束最优化问题，采用Wolfe线搜索和armijo算法，还有对各种修正方法（HS，DY...）的对比【自己编写的】-Conjugate Gradient Methods Solve Optimal Question And Linear Eqution
numerical-experiment-one
- 最优化最速下降方法，利用了非精确步长搜索 armijo、Wolfe方式，并利用两个算例进行演示-Optimization of steepest descent method, using the inexact search step length armijo, Wolfe method, and the use of two examples for demonstration
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- 最优化方法——线搜索源代码 包含Armijo准则、0.618法精确线搜索-Optimization method- line search source code
优化算法
- 解决了最小无约束优化问题 步长由ARmijo非精确一维搜索生成，迭代方向分别由最速下降法，阻尼牛顿法，共轭梯度法，拟牛顿法(BFGS)产生(This code solves the minimum unconstrained optimization problem, and the step size is generated by ARmijo inexact one-dimensional search. The iterative directions are generated b
armijo线搜索+最速下降法的小程序
- armijo线搜索+最速下降法的小程序erfwefwerfwqrfw(Armijo line search + steepest descent algorithm appletfvv ewrwefg)
第一题bfgs
- armijo准则下bfgs法实现，最优化方法作业，大连理工大学(Realization of BFGS method under Armijo criterion, operation of optimization method, Dalian University of Technology)