Stable Matchings in Practice: A Constraint Programming Approach

Fuente: arXiv
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Auteurs principaux: Sun, Zhaohong, Yamada, Naoyuki, Takenami, Yoshihiro, Moriwaki, Daisuke, Yokoo, Makoto
Format: Preprint
Publié: 2024
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author Sun, Zhaohong
Yamada, Naoyuki
Takenami, Yoshihiro
Moriwaki, Daisuke
Yokoo, Makoto
author_facet Sun, Zhaohong
Yamada, Naoyuki
Takenami, Yoshihiro
Moriwaki, Daisuke
Yokoo, Makoto
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2401_07761
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Stable Matchings in Practice: A Constraint Programming Approach
Sun, Zhaohong
Yamada, Naoyuki
Takenami, Yoshihiro
Moriwaki, Daisuke
Yokoo, Makoto
Computer Science and Game Theory
91B68
F.2; I.2
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.
title Stable Matchings in Practice: A Constraint Programming Approach
topic Computer Science and Game Theory
91B68
F.2; I.2
url https://arxiv.org/abs/2401.07761