Reference:
Menzies, T., Chen, T., Ye, Y., Ganguly, K. K., Rayegan, A., & Srinivasan, S. (2025).
MOOT: A repository of many multi-objective optimization tasks (Version 2025) [Data set].
Zenodo. https://doi.org/10.5281/zenodo.17354083
@misc{menzies2025mootrepositorymultiobjectiveoptimization,
title={MOOT: a Repository of Many Multi-Objective Optimization Tasks},
author={Tim Menzies and Tao Chen and Yulong Ye and Kishan Kumar Ganguly and Amirali Rayegan and Srinath Srinivasan and Andre Lustosa},
year={2025},
eprint={2511.16882},
archivePrefix={arXiv},
primaryClass={cs.SE},
url={https://arxiv.org/abs/2511.16882},
}Moot is such a good name for datasets to be used to assess different algorithms. Its definition is
(noun) a mock trial set up to examine a hypothetical case as an academic exercise. "the object of a moot is to provide practice in developing an argument"