User Guide for Modularized Surrogate Model Toolbox
Müller, Juliane (2012)
Tampere University of Technology
2012
Luonnontieteiden ja ympäristötekniikan tiedekunta - Faculty of Science and Environmental Engineering
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201610044581
https://urn.fi/URN:NBN:fi:tty-201610044581
Tiivistelmä
This user guide accompanies the surrogate model toolbox for global optimization problems. The toolbox is made for computationally expensive black-box global optimization problems with continuous, integer, or mixed-integer variables. Problems where several or all variables have to be integers may also have black-box constraints, whereas purely continuous problems may only have box constraints.
For problems with computationally cheap function evaluations the toolbox may not be very efficient. Surrogate models are intended to be used when function evaluations take from several minutes to several hours or more. When reading this manual it is recommended to simultaneously take a look at the code.
The code is set up such that the user only has to define his/her optimization problem in a Matlab file (see Section 6.1). Additional input such as the surrogate model to be used, the sampling strategy, or starting points are optional (see Section 6).
This document is structured as follows. In Section 2 the general structure of a surrogate model algorithm is summarized. The installation is described in Section 3. The dependencies of the single functions in the code are shown in Section 4. Section 5 briefly summarizes how the surrogate model algorithm works in general. Section 6 describes the options for the input of the main function. In Section 7 the input and output of the single subfunctions of the algorithm are described. Examples for using the surrogate model algorithm are given in Section 8. In Section 9 it is explained how the user can define an own (mixture) surrogate model and an example is given. The elements of the saved results are described in Section 10.
For problems with computationally cheap function evaluations the toolbox may not be very efficient. Surrogate models are intended to be used when function evaluations take from several minutes to several hours or more. When reading this manual it is recommended to simultaneously take a look at the code.
The code is set up such that the user only has to define his/her optimization problem in a Matlab file (see Section 6.1). Additional input such as the surrogate model to be used, the sampling strategy, or starting points are optional (see Section 6).
This document is structured as follows. In Section 2 the general structure of a surrogate model algorithm is summarized. The installation is described in Section 3. The dependencies of the single functions in the code are shown in Section 4. Section 5 briefly summarizes how the surrogate model algorithm works in general. Section 6 describes the options for the input of the main function. In Section 7 the input and output of the single subfunctions of the algorithm are described. Examples for using the surrogate model algorithm are given in Section 8. In Section 9 it is explained how the user can define an own (mixture) surrogate model and an example is given. The elements of the saved results are described in Section 10.