<< uncprb_getinitf Unconstrained Optimization Problems Toolbox uncprb_getname >>

Unconstrained Optimization Problems Toolbox >> Unconstrained Optimization Problems Toolbox > uncprb_getinitpt

uncprb_getinitpt

Returns the starting point.

Calling Sequence

[n,m,x]=uncprb_getinitpt(nprob)
[n,m,x]=uncprb_getinitpt(nprob,fact)

Parameters

nprob:

the problem number

fact:

a 1 x 1 matrix of doubles, multiplier for the coordinate of x0 (default = 1)

n:

the number of variables, i.e. the size of x

m:

the number of functions, i.e. the size of fvec

x:

a n x 1 matrix of doubles, the (multiplied) starting point

Description

This function generates the starting points for each problem by calling the function initf, which sets m, n and the starting point xo for the number of problem given to it. If xo is the standard starting point, then x will contain fact*xo, except if xo is the zero vector and fact is not unity, then all the components of x will be set to fact.

Examples

// Get starting data for Rosenbrock's test case
// n=2, m=2, x=[-1.2,1]'
nprob = 1
[n,m,x]=uncprb_getinitpt(nprob)

// Get starting data for Rosenbrock's test case
// Multiplies x0 by 3
[n,m,x]=uncprb_getinitpt(nprob,3)

// Get a sequence of starting points,
// increasingly away from the usual one.
nprob = 1
alpha = 5
ntries = 10
fact = 1
for k = 1 : ntries
[n,m,x0]=uncprb_getinitpt(nprob,fact);
fact = alpha * fact;
disp([k x0'])
end

// Get a sequence of starting points,
// randomly in the neighbourhood of the usual one.
nprob = 1
ntries = 10
len = 2
[n,m,x0]=uncprb_getinitpt(nprob);
plot ( x0(1) , x0(2) , "ro" )
for k = 1 : ntries
[n,m,x0]=uncprb_getinitpt(nprob);
x0 = x0 + len * (2*rand(n,1)-1);
disp([k x0'])
plot ( x0(1) , x0(2) , "b*" )
end

Authors

<< uncprb_getinitf Unconstrained Optimization Problems Toolbox uncprb_getname >>