« Previous « Start » Next »
14 GLB Problem
The
unconstrained global optimization (
glb) problem
is defined as
where
x,
xL,
xU 
Rn,
f(
x)
R.
The following files define a problem in TOMLAB.
File: tomlab/quickguide/glbQG_f.m
f: Function
The following file illustrates how to solve an unconstrained
global optimization problem in TOMLAB. Also view the m-file
specified above for more information.
File: tomlab/quickguide/glbQG.m
Open the file for viewing, and execute glbQG in Matlab.
% glbQG is a small example problem for defining and solving
% unconstrained global programming problems using the TOMLAB format.
Name = 'Shekel 5';
x_L = [ 0 0 0 0]'; % Lower bounds for x.
x_U = [10 10 10 10]'; % Upper bounds for x.
x_0 = [-3.0144 -2.4794 -3.1584 -3.1790]; % May not be used.
x_opt = [];
f_opt = -10.1531996790582;
f_Low=-20; % Lower bound on function.
x_min = [ 0 0 0 0]; % For plotting
x_max = [10 10 10 10]; % For plotting
Prob = glcAssign('glbQG_f', x_L, x_U, Name, [], [], [], ...
[], [], [], x_0, ...
[], [], [], [], ...
f_Low, x_min, x_max, f_opt, x_opt);
Prob.optParam.MaxFunc = 1500;
Result1 = tomRun('glbFast', Prob, 1); %Global solver
Result2 = tomRun('conSolve', Prob, 1); %Local solver
% Result = tomRun('glbSolve', Prob, 1);
% Result = tomRun('glcSolve', Prob, 1);
% Result = tomRun('glcFast', Prob, 1);
% Result = tomRun('lgo', Prob, 1);
% Result = tomRun('oqnlp', Prob, 1);
« Previous « Start » Next »
TOMLAB
