Finding Robust Solutions to Stable Marriage

Begum Genc (1) , Mohamed Siala (1) , Gilles Simonin (2, 3) , Barry O ' Sullivan (1)

1 INSIGHT - Insight Centre for Data Analytics
2 IMT Atlantique - DAPI - Département Automatique, Productique et Informatique
3 LS2N - équipe TASC - Théorie, Algorithmes et Systèmes en Contraintes

We study the notion of robustness in stable matching problems. We first define robustness by introducing (a, b)-supermatches. An (a, b)-supermatch is a stable matching in which if a pairs break up it is possible to find another stable matching by changing the partners of those a pairs and at most b other pairs. In this context, we define the most robust stable matching as a (1, b)-supermatch where b is minimum. We show that checking whether a given stable matching is a (1, b)-supermatch can be done in polynomial time. Next, we use this procedure to design a constraint programming model, a local search approach, and a genetic algorithm to find the most robust stable matching. Our empirical evaluation on large instances show that local search out-performs the other approaches.

Domaines: Informatique [cs]; Intelligence artificielle [cs.AI]; Recherche opérationnelle [math.OC]

Begum Genc, Mohamed Siala, Gilles Simonin, Barry O ' Sullivan. Finding Robust Solutions to Stable Marriage. IJCAI 2017, Aug 2017, Melbourne, Australia. ⟨hal-01689897⟩