Quickguide GLB Problem: Difference between revisions
(Created page with "{{Part Of Manual|title=the Quickguide Manual|link=Quickguide}} The '''unconstrained global optimization''' ('''glb''') problem is defined as <math> \begin{arra...") |
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where <math>x, x_L, x_U \in \ | where <math>x, x_L, x_U \in \mathbb{R}^n</math>, <math>f(x) \in \mathbb{R}</math>. | ||
The following files define a problem in TOMLAB. | The following files define a problem in TOMLAB. | ||
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Open the file for viewing, and execute glbQG in Matlab. | Open the file for viewing, and execute glbQG in Matlab. | ||
< | <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> | ||
Latest revision as of 06:51, 17 January 2012
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This page is part of the Quickguide Manual. See Quickguide. |
The unconstrained global optimization (glb) problem is defined as
Failed to parse (SVG with PNG fallback (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle \begin{array}{ll} \min\limits_{x} & f(x) \\ & \\ s/t & \begin{array}{llcccll} -\infty < &x_{L} & \leq & x & \leq & x_{U}& < \infty \\ \end{array} \end{array} }
where Failed to parse (SVG with PNG fallback (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle x, x_L, x_U \in \mathbb{R}^n}
, Failed to parse (SVG with PNG fallback (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle f(x) \in \mathbb{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]; % Most often not 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, 2); % Local solver, starting from Prob.x_0
% Also possible to use a mixed-integer global solver
Result = tomRun('glcDirect', Prob, 1);
% Result = tomRun('glbDirect', Prob, 1);
% Result = tomRun('glcDirect', Prob, 1);
% 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);