In this repository, we gather code, experimental setups, and results for attempting to pre-condition multi-objective optimization problems (MOOPs).
In this repository, you will find:
- Notebooks (R) - Notebooks that can be (re-)run by
users to reproduce our results. All results are included, such that
the notebooks will only recompute them if you delete them. The
notebooks are very detailed and document all steps necessary.
- An Approach to Ordering Objectives and Pareto Efficient Solutions - A second notebook focusing on a low- or no-preference approach to ordering Pareto efficient solutions and single objectives. There exists a paper-like render of this notebook on arXiv for the time being https://doi.org/10.48550/arXiv.2205.15291 (Hönel and Löwe 2022).
- Pre-conditioning of multi-objective optimization problems - The first notebook of this repository.
- Results (RDS) - All data required for reproduction is included. All the results, too. Some of these may take a long time to compute, so be aware.
Hönel, Sebastian, and Welf Löwe. 2022. “An Approach to Ordering Objectives and Pareto Efficient Solutions.” arXiv. https://doi.org/10.48550/arXiv.2205.15291.