Optimization: principles and algorithms, by Michel Bierlaire
Functions
conjugateGradient.m File Reference

Algorithm 9.2: Conjugate gradient algorithm for quadratic problems. More...

Go to the source code of this file.

Functions

function conjugateGradient (in Q, in b, in x0, in printlevel)
 Applies the conjugate gradient method to solve

\[\min_x \frac{1}{2} x^T Q x + b^T x\]

where $Q \in \mathbb{R}^n\times\mathbb{R}^n $ and $b \in \mathbb{R}^n$. More...

 

Detailed Description

Algorithm 9.2: Conjugate gradient algorithm for quadratic problems.

Implementation of algorithm 9.2 of [1]

Author
Michel Bierlaire
Date
Sat Apr 5 23:32:26 2014

Definition in file conjugateGradient.m.

Function Documentation

function conjugateGradient ( in  Q,
in  b,
in  x0,
in  printlevel 
)

Applies the conjugate gradient method to solve

\[\min_x \frac{1}{2} x^T Q x + b^T x\]

where $Q \in \mathbb{R}^n\times\mathbb{R}^n $ and $b \in \mathbb{R}^n$.

Note
Tested with run0908cg.m
Called by newtonLocalQuadratic
Parameters
Qmatrix of size $n \times n $.
bvector of size $n$.
x0starting point
printlevelif different from 0, informations are printed at each iteration (Default: 0)
Returns
[D, solution]
D: matrix gathering all directions generated by the algorithms
solution: optimal solution
Copyright 2015-2016 Michel Bierlaire