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24 SIM Problem
Simulation problems can be of any problem type, but in general they
are global black-box problem interfacing an external simulator. The
setup may require that objective values and constraints are
evaluated simultaneously. To accommodate this in TOMLAB a special
assign routine has been developed,
simAssign. The solver
execution will be much more efficient if using this assign routine.
The simulation problem is identical to the mixed-integer nonlinear
programming problem defined as:
|
|
|
f(x) |
| |
|
| s/t |
| xL |
≤ |
x |
≤ |
xU |
| bL |
≤ |
A x |
≤ |
bU |
| cL |
≤ |
c(x) |
≤ |
cU |
|
|
(26) |
where
x,
xL,
xU 
Rn,
f(
x)
R,
A
Rm1 × n,
bL,
bU Rm1 and
cL,
c(
x),
cU Rm2. The variables
x I, the
index subset of 1,...,
n, are restricted to be integers.
Example problem:
The following files define a problem in TOMLAB.
File: tomlab/quickguide/simQG.m, simQG_fc.m, simQG_gdc.m
fc: Function value and nonlinear constraint vector
gdc: Gradient vector and nonlinear constraint gradient matrix
The following file illustrates how to solve this simulation (SIM)
problem in TOMLAB. Also view the m-files specified above for more
information.
File: tomlab/quickguide/simQG.m
Open the file for viewing, and execute simQG in Matlab.
% simQG is a small example problem for defining and solving simulation
% problems where the objective function and constraints are evaluated
% during the same function call.
Name = 'HS 47';
b_L = [];
b_U = [];
A = [];
c_L = [0; 0; 0];
c_U = [0; 0; 0];
x_0 = [2; sqrt(2); -1; 2-sqrt(2); .5];
x_L = [];
x_U = [];
Prob = simAssign('simQG_fc', 'simQG_gdc', [], [], x_L, x_U, ...
Name, x_0, [], A, b_L, b_U, [], c_L, c_U);
Result = tomRun('snopt', Prob, 1);
% Prob.KNITRO.options.HESSOPT = 6;
% Prob.KNITRO.options.ALG = 3;
% Result2 = tomRun('knitro', Prob, 1);
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