Models Global Optimization Problems: glb prob, lgo1 prob, lgo2 prob and gkls prob: Difference between revisions
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'''File: '''tomlab/quickguide/glbQG.m | '''File: '''tomlab/quickguide/glbQG.m | ||
< | <source lang="matlab"> | ||
% glbQG is a small example problem for defining and solving | % glbQG is a small example problem for defining and solving | ||
% unconstrained global programming problems using the TOMLAB format. | % unconstrained global programming problems using the TOMLAB format. | ||
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% Result = tomRun('lgo', Prob, 1); | % Result = tomRun('lgo', Prob, 1); | ||
% Result = tomRun('oqnlp', Prob, 1); | % Result = tomRun('oqnlp', Prob, 1); | ||
</ | </source> | ||
==glb_prob== | ==glb_prob== |
Latest revision as of 13:55, 22 January 2012
Example of a global optimization problem
The basic structure of a global optimization problem with simple bounds is the following
where , . The variables , the index subset of , are restricted to be integers.
The following file is required to define a problem of this category in TOMLAB.
File: tomlab/quickguide/glbQGf.m
f: Function
An example of a problem of this class, (that is also found in the TOMLAB quickguide) is glbQG:
File: tomlab/quickguide/glbQG.m
% 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);
glb_prob
In glb_prob there are 51 unconstrained global optimization test problems with sizes to 100 variables. In order to define the problem n and solve it execute the following in Matlab:
Prob = probInit('glb_prob',n); Result = tomRun('',Prob);
lgo1_prob
In glo1_prob there are 30 global optimization test problems in one dimension. In order to define the problem n and solve it execute the following in Matlab:
Prob = probInit('lgo1_prob',n); Result = tomRun('',Prob);
lgo2_prob
In glo2_prob there are 30 global optimization test problems in two up to four dimensions. In order to define the problem n and solve it execute the following in Matlab:
Prob = probInit('lgo2_prob',n); Result = tomRun('',Prob);
gkls_prob
In gkls_prob there are 300 global optimization test problems in two dimensions. In order to define the problem n and solve it execute the following in Matlab:
Prob = probInit('gkls_prob',n); Result = tomRun('',Prob);