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

Algorithm 11.6: Steepest descent algorithm. More...

Go to the source code of this file.

Functions

function steepestDescent (in obj, in x0, in eps, in maxiter)
 Applies the steepest descent algorithm with linesearch to solve $\min_x f(x)$ where $f:\mathbb{R}^n\to\mathbb{R}$. More...
 

Detailed Description

Algorithm 11.6: Steepest descent algorithm.

Implementation of algorithm 11.6 of [1]

Author
Michel Bierlaire
Date
Fri Mar 20 17:03:30 2015

Definition in file steepestDescent.m.

Function Documentation

function steepestDescent ( in  obj,
in  x0,
in  eps,
in  maxiter 
)

Applies the steepest descent algorithm with linesearch to solve $\min_x f(x)$ where $f:\mathbb{R}^n\to\mathbb{R}$.

Note
Tested with runRosenbrockSteepestDescent.m
Calls lineSearch
Parameters
objthe name of the Octave function defining f(x) and its derivatives
x0the starting point
epsalgorithm stops if $\|F(x)\| \leq \varepsilon $.
maxitermaximum number of iterations (Default: 100)
Returns
[solution,iteres,niter]
solution: local minimum of the function
iteres: sequence of iterates generated by the algorithm. It contains n+2 columns. Columns 1:n contains the value of the current iterate. Column n+1 contains the value of the objective function. Column n+2 contains the value of the norm of the gradient. It contains maxiter rows, but only the first niter rows are meaningful.
niter: total number of iterations
Copyright 2015-2016 Michel Bierlaire