## 14GLB Problem

The unconstrained global optimization (glb) problem is defined as
 min x
f(x)

s/t
 −∞ < xL ≤ x ≤ xU < ∞
(16)
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);```