Dichotomy Results for Classified Rank-Maximal Matchings and Popular Matchings
Meghana Nasre, Prajakta Nimbhorkar, Nada Pulath

TL;DR
This paper investigates optimal matchings in bipartite graphs with preferences, capacities, and classifications, providing efficient algorithms for laminar cases and proving NP-hardness for non-laminar cases, along with a dichotomy for popular matchings.
Contribution
It introduces a polynomial-time algorithm for rank-maximal matchings with laminar classifications and establishes NP-hardness for non-laminar cases, also presenting a dichotomy for popular matchings.
Findings
Polynomial-time algorithm for laminar classifications
NP-hardness for non-laminar classifications
Dichotomy result for popular matchings
Abstract
In this paper, we consider the problem of computing an optimal matching in a bipartite graph where elements of one side of the bipartition specify preferences over the other side, and one or both sides can have capacities and classifications. The input instance is a bipartite graph G=(A U P,E), where A is a set of applicants, P is a set of posts, and each applicant ranks its neighbors in an order of preference, possibly involving ties. Moreover, each vertex v in A U P has a quota q(v) denoting the maximum number of partners it can have in any allocation of applicants to posts - referred to as a {\em matching} in this paper. A classification for a vertex u is a collection of subsets of neighbors of u. Each subset (class) has an upper quota denoting the maximum number of vertices from the class that can be matched to u. The goal is to find a matching that is optimal amongst all the…
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Taxonomy
TopicsGame Theory and Voting Systems · Names, Identity, and Discrimination Research · Bayesian Modeling and Causal Inference
