OUTDOOR (Open Superstructure Modeling and Optimization Framework) is a comprehensive tool for constructing and solving superstructure optimization models using Mixed Integer Linear Programming (MILP) solvers.
- Modular Component Library: The outdoor_core module provides classes for unit operations (reactors, stream splitters, etc.) and system data components that can be assembled into custom superstructures.
- Integrated MILP Solver: Built-in PYOMO abstract model implementation that can be applied to various applications including biorefineries, chemical processing, and Power-to-X technologies.
- User-Friendly Interface: Create models through Python scripting with intuitive APIs or use the Excel-based interface for rapid model development.
- Visualization and Analysis: Integrated tools for reviewing model structure, analyzing results, and optimizing processes.
pip install outdoor
For the latest development version:
pip install git+https://github.com/llvdrhau/OUTDOOR_USC.git
OUTDOOR provides multiple ways to define your superstructure models:
- Excel Templates: Use predefined templates to configure your models
- GUI Interface: Visual modeling environment (if available in your installation)
OUTDOOR is available under a Dual commercial license. Free usage is permitted under the GNU General Public License (GPL) v3.0 for academic and non-commercial purposes. For commercial use, please reach out to lucasvdhauwaert@gmail.com. See the [Commercial License Agreement](COMMERCIAL_LICENSE.md) for details.
For full documentation, visit: [Documentation Link, under construction]
To contribute to OUTDOOR:
- Clone the repository
- Install development dependencies: pip install -e ".[dev]"
- Run tests: pytest (proper test need to still be made)
If you wish to use this software, please cite:
@article{van_der_hauwaert_et_al,
title = {Designing Sustainable Biorefineries for Agricultural Waste: An Environmental-Economic Optimization of Tomato Pomace},
author = {Van der Hauwaert, Lucas and Sommer Schjønberg, Mias and Regueira Lopez, Alberte and Mauricio-Iglesias, Miguel},
journal = {Preprint available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5277124}
}
For support or inquiries, please contact lucasvdhauwaert@gmail.com