Description: Surrogate model toolbox for
- unconstrained continuous
- constrained integer
- constrained mixed-integer
global optimization problems that are computationally expensive.
The user can choose beween different options for
- the surrogate model
- the sampling strategy
- the initial experimental design
The user can determine the maximum number of allowed function evaluations, the number of points in the initial starting design, and one or more points that are added to the starting design.
The algorithm is useful when a single function evaluation is very time-consuming and therefore good approximations of the global optimum must be found within a very restricted number of evaluations.
How so you use this if you have a series of x1 x2 x3 and y data?
This package is very useful
This toolbox is very helpful for me. Thanks for the author.
Any hints and examples for parallel object and constraints functions evaluations?
Is posible to use general nonlinear constraints at mixed-integer mode without any integer variables ... to solve pure continuous problems with constraints?
Why are not included nonlinear constraints for continous problems???
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