= Welcome to the RBFOpt Wiki =
'''RBFOpt''' is a software for '''black-box''' (also known as ''derivative-free'') optimization. It deals with problems of this form:
{{{
min f(x)
s.t. x_L <= x <= x_U
x_i in Z for all i in I and,
x_i in R for all i not in I.
}}}
It does ''not'' assume that {{{f(x)}}} is known in analytical form: {{{f(x)}}} is simply a black-box that, given input values, produces output values. The bounds on the variables {{{x_L, x_U}}} are assumed to be finite. '''RBFOpt''' is especially targeted at problems for which each evaluation of the objective function {{{f(x)}}} is expensive (in terms of computing time, or cost, or some other measure) and we want to find a ''global'' minimum of the function with as few function evaluations as possible. Since this is a very difficult class of problems (we do not assume availability of first order derivatives), '''RBFOpt''' works best on problems that are relatively small dimensional (a 10-40 variables) and for which the bounding box is not too large. However, it has been successfully employed on problems on much larger sizes.
'''RBFOpt''' is implemented in Python 3 and 2.7. For questions that are not answered by the user documentation, you can use the [http://list.coin-or.org/mailman/listinfo/rbfopt official mailing list].
== Downloads ==
The main '''RBFOpt''' repository is hosted on '''!GitHub'''. The official page is:
[https://github.com/coin-or/rbfopt]
You can download the latest trunk version by obtaining a copy of the repository. Alternatively, you can download one of the available releases. Installation instructions are available together with the source on !GitHub.
== Documentation ==
Documentation for the library is available on '''!ReadTheDocs'''. The HTML and PDF version are automatically built whenever the code is updated on !GitHub. We recommend the HTML version, as it is easier to navigate.
[http://rbfopt.readthedocs.org/en/latest/]
== Authors and contributors ==
Authors:
* Giacomo Nannicini : project manager, main developer. [http://researcher.watson.ibm.com/researcher/view.php?person=us-nannicini]
Contributors:
* Alberto Costa : numerical testing, useful discussion and ideas. [http://www.lix.polytechnique.fr/~costa/]
* Giorgio Sartor : numerical testing, useful discussion and ideas.
== Contribute ==
Development of the library takes place on !GitHub. You can contribute to the software on !GitHub.
You can also use this page to [https://projects.coin-or.org/RBFOpt/newticket submit a ticket] if you find a bug.
== Referencing RBFOpt ==
If you use RBFOpt, we would be grateful if you could cite the following paper (this list will be updated from time to time):
A. Costa and G. Nannicini. ''RBFOpt: an open-source library for black-box optimization with costly function evaluations.'' Optimization Online, paper 4538.