---
title: "New Algorithms for Japanese Residency Matching"
authors:
  - "Zhaohong Sun"
  - "Taiki Todo"
  - "Makoto Yokoo"
doi: "10.24963/ijcai.2021/58"
url: "https://ijcai.org/proceedings/2021/58"
pdf: "https://ijcai.org/proceedings/2021/0058.pdf"
venue: "Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence"
year: 2021
pages: "412-418"
track: "Main Track"
keywords:
  - "Agent-based and Multi-agent Systems: Economic Paradigms, Auctions and Market-Based Systems"
---

# New Algorithms for Japanese Residency Matching

Zhaohong Sun, Taiki Todo, Makoto Yokoo

*Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence*, pages 412-418. DOI: [10.24963/ijcai.2021/58](https://doi.org/10.24963/ijcai.2021/58)

## Abstract

We study the Japanese Residency Matching Program (JRMP) in which hospitals are partitioned into disjoint regions and both hospitals and regions are subject to quotas. To achieve a balanced distribution of doctors across regions, hard bounds are imposed by the government to limit the number of
doctors who can be placed in each region. However, such hard bounds lead to inefficiency in terms of wasted vacant positions. In this paper, we propose
two suitable algorithms to reduce waste with minimal modification to the current system and show that they are superior to the algorithm currently
deployed in JRMP by comparing them theoretically and empirically.