CGO arbfMIP
This page is part of the CGO Manual. See CGO Manual. |
Purpose
Solve general constrained mixed-integer global black-box optimization problems with costly objective functions.
The optimization problem is of the following form
where ; ;
the linear constraints are defined by , ;
and the nonlinear constraints are defined by .
The variables are restricted to be integers,
where is an index subset of possibly empty.
It is assumed that the function is continuous with respect to all
variables, even if there is a demand that some variables only take integer values.
Otherwise it would not make sense to do the surrogate modeling of used by all CGO solvers.
f (x) is assumed to be a costly function while c(x) is assumed to be cheaply computed. Any costly constraints can be treated by adding penalty terms to the objective function in the following way:
where weighting parameters wj have been added. The user then returns p(x) instead of f (x) to the CGO solver.
Calling Syntax
Result = arbfMIP(Prob,varargin) Result = tomRun('arbfMIP', Prob);
Description of Inputs
Problem structure
The following fields are used in the problem description structure Prob:
Input | Description |
---|---|
Name | See Common input for all CGO solvers |
FUNCS.f | |
FUNCS.c | |
x_L | |
x_U | |
b_L | |
b_U | |
A | |
c_L | |
c_U | |
WarmStart | |
MaxCPU | |
user | |
PriLevOpt | |
f_Low | |
optParam | |
CGO | See the table below but also this table for input common to all CGO solvers |
GO | See common input for all CGO solvers |
MIP | See common input for all CGO solvers |
varargin | Additional parameters to arbfmip are sent to the costly f(x) |
- Special ARBF algorithm parameters in Prob.CGO - | |||||||||||||||
rbfType | Selects type of radial basis function
| ||||||||||||||
infStep | If =1, add search step with target value -inffirst in cycle. Default 0 | ||||||||||||||
TargetMin | Which minimum of several to pick in target value problem:
Default is TargetMin = 3. | ||||||||||||||
fStarRule | Global-Local search strategy. N = cycle length. Define min_sn as the global minimum on surface.
Strategy names in Gutmanns thesis: III, II, I | ||||||||||||||
DeltaRule | 1 = Skip large f(x) when computing f(x) interval Delta. 0 = Use all points. If objType > 0, default DeltaRule = 0, otherwise default is 1. | ||||||||||||||
eps_sn | Relative tolerance used to test if the minimum of surface, min_sn, is sufficiently lower than the best point (fMin) found. Default is eps_sn = 10-7. |
Description of Outputs
Result structure
The output structure Result contains results from the optimization.
The following fields are set:
Field | Description | ||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
x_k | See Common output for all CGO solvers for details. | ||||||||||||||||
f_k | |||||||||||||||||
Iter | |||||||||||||||||
FuncEv | |||||||||||||||||
ExitText | |||||||||||||||||
ExitFlag | Always 0 | ||||||||||||||||
Inform | Information parameter.
| ||||||||||||||||
CGO | Subfield WarmStartInfo saves warm start information, the same information as in cgoSave.mat, see Common output for all CGO solvers#WSInfo. |
Description
arbfMIP implements the Adaptive Radial Basis Function (ARBF) algorithm. The ARBF method handles linear equality and inequality constraints, and nonlinear equality and inequality constraints, as well as mixed-integer problems.
M-files Used
daceInit.m, iniSolve.m, endSolve.m, conAssign.m, glcAssign.m, snSolve.m, gnSolve.m, expDesign.m.
MEX-files Used
tomsol
See Also
rbfSolve.m and ego.m
Warnings
Observe that when cancelling with CTRL+C during a run, some memory allocated by arbfMIP will not be deallocated. To deallocate, do:
''>> ''clear cgolib