TY - JOUR
T1 - Stable Matchings in Practice
T2 - 38th AAAI Conference on Artificial Intelligence, AAAI 2024
AU - Sun, Zhaohong
AU - Yamada, Naoyuki
AU - Takenami, Yoshihiro
AU - Moriwaki, Daisuke
AU - Yokoo, Makoto
N1 - Publisher Copyright:
© 2024, Association for the Advancement of Artifcial Intelligence (www.aaai.org). All rights reserved.
PY - 2024/3/25
Y1 - 2024/3/25
N2 - We study a practical two-sided matching problem of allocating children to daycare centers, which has significant social implications. We are cooperating with several municipalities in Japan and our goal is to devise a reliable and trustworthy clearing algorithm to deal with the problem. In this paper, we describe the design of our new algorithm that minimizes the number of unmatched children while ensuring stability. We evaluate our algorithm using real-life data sets, and experimental results demonstrate that our algorithm surpasses the commercial software that currently dominates the market in terms of both the number of matched children and the number of blocking coalitions (measuring stability). Our findings have been reported to local governments, and some are considering adopting our proposed algorithm in the near future, instead of the existing solution. Moreover, our model and algorithm have broader applicability to other important matching markets, such as hospital-doctor matching with couples and school choice with siblings.
AB - We study a practical two-sided matching problem of allocating children to daycare centers, which has significant social implications. We are cooperating with several municipalities in Japan and our goal is to devise a reliable and trustworthy clearing algorithm to deal with the problem. In this paper, we describe the design of our new algorithm that minimizes the number of unmatched children while ensuring stability. We evaluate our algorithm using real-life data sets, and experimental results demonstrate that our algorithm surpasses the commercial software that currently dominates the market in terms of both the number of matched children and the number of blocking coalitions (measuring stability). Our findings have been reported to local governments, and some are considering adopting our proposed algorithm in the near future, instead of the existing solution. Moreover, our model and algorithm have broader applicability to other important matching markets, such as hospital-doctor matching with couples and school choice with siblings.
UR - http://www.scopus.com/inward/record.url?scp=85189607417&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85189607417&partnerID=8YFLogxK
U2 - 10.1609/aaai.v38i20.30244
DO - 10.1609/aaai.v38i20.30244
M3 - Conference article
AN - SCOPUS:85189607417
SN - 2159-5399
VL - 38
SP - 22377
EP - 22384
JO - Proceedings of the AAAI Conference on Artificial Intelligence
JF - Proceedings of the AAAI Conference on Artificial Intelligence
IS - 20
Y2 - 20 February 2024 through 27 February 2024
ER -