treeopt

A python module for simulation-based optimization.

Project Features

This project is currently under development and in a very experimental state. The goal is to provide a simulation-based optimization framework. The functionality builds on the tools from the following libraries.

• Metamodelling features from the Surrogate Modeling Toolbox.
• Optimization tools from SciPy

Getting Started

Install using

pip install git+https://github.com/hbrs-cse/treeopt.git

and check out the examples.

The project's documentation contains a section to help you get started as a developer or user of the library. Read the Contribution Guide if you would like to contribute to the project.

Resources

Below are some handy resource links.

• Project Documentation
• Surrogate Modeling Toolbox
• SciPy
• Click is a Python package for creating beautiful command line interfaces in a composable way with as little code as necessary.
• Sphinx is a tool that makes it easy to create intelligent and beautiful documentation, written by Geog Brandl and licnsed under the BSD license.
• pytest helps you write better programs.
• GNU Make is a tool which controls the generation of executables and other non-source files of a program from the program's source files.

Authors

• Alexander Busch - Author - github
• Jan Kleinert - Initial work - github

See also the list of contributors who participated in this project.