Refined Computational Complexities of Hospitals/Residents Problem with Regional Caps

TL;DR

This paper analyzes the computational complexity of the Hospitals/Residents problem with regional caps, identifying which cases are computationally feasible and which are NP-complete based on various parameters.

Contribution

It refines previous complexity results by classifying tractable and intractable cases of HRRC based on preference list length, region size, and overlap.

Findings

Classifies cases of HRRC as tractable or NP-complete

Identifies parameters affecting computational complexity

Provides a complete complexity classification for HRRC

Abstract

The Hospitals/Residents problem (HR) is a many-to-one matching problem whose solution concept is stability. It is widely used in assignment systems such as assigning medical students (residents) to hospitals. To resolve imbalance in the number of residents assigned to hospitals, an extension called HR with regional caps (HRRC) was introduced. In this problem, a positive integer (called a regional cap) is associated with a subset of hospitals (called a region), and the total number of residents assigned to hospitals in a region must be at most its regional cap. Kamada and Kojima defined strong stability for HRRC and demonstrated that a strongly stable matching does not necessarily exist. Recently, Aziz et al. proved that the problem of determining if a strongly stable matching exists is NP-complete in general. In this paper, we refine Aziz et al.'s result by investigating the computational complexity of the problem in terms of the length of preference lists, the size of regions, and whether or not regions can overlap, and completely classify tractable and intractable cases.