Polynomial Time Presolve Algorithms for Rotation-Based Models Solving the Robust Stable Matching Problem
Sulian Le Bozec-Chiffoleau, Charles Prud'homme, Gilles Simonin
Abstract
The Robust Stable Matching (RSM) problem involves finding a stable matching that allows getting another stable matching within a minimum number of changes when a pair becomes forbidden. It has been shown that such a problem is NP-Hard. In this paper, we enrich the mathematical model for the RSM problem based on new theoretical properties. We derive from these properties new polynomial time pre-solving algorithms which both reduce the search space and speed up the exploration. We also extend our results to the instances of the Many-to-Many problem and give its corresponding constraint programming (CP) model. We show how the use of our algorithms improve the state-of-the-art results and make it possible to obtain proofs of optimality on large instances via the CP model.
BibTeX
@inproceedings{ijcai2024p317,
title = {Polynomial Time Presolve Algorithms for Rotation-Based Models Solving the Robust Stable Matching Problem},
author = {Le Bozec-Chiffoleau, Sulian and Prud'homme, Charles and Simonin, Gilles},
booktitle = {Proceedings of the Thirty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-24}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Kate Larson},
pages = {2860--2867},
year = {2024},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2024/317},
url = {https://doi.org/10.24963/ijcai.2024/317},
}