Manipulation Strategies for the Rank Maximal Matching Problem
Pratik Ghosal, Katarzyna Paluch

TL;DR
This paper explores how applicants can strategically falsify preferences in rank-maximal matchings to improve their outcomes, analyzing manipulation strategies and their potential effects on matching results.
Contribution
It introduces new manipulation strategies for applicants to influence rank-maximal matchings, considering both worst-case and best-case outcome improvements.
Findings
Manipulation can alter the matching outcome in favor of the manipulative applicant.
Strategies can guarantee no worse matches or improve the best possible match.
Computational complexity of manipulation strategies is analyzed.
Abstract
We consider manipulation strategies for the rank-maximal matching problem. In the rank-maximal matching problem we are given a bipartite graph such that denotes a set of applicants and a set of posts. Each applicant has a preference list over the set of his neighbours in , possibly involving ties. Preference lists are represented by ranks on the edges - an edge has rank , denoted as , if post belongs to one of 's -th choices. A rank-maximal matching is one in which the maximum number of applicants is matched to their rank one posts and subject to this condition, the maximum number of applicants is matched to their rank two posts, and so on. A rank-maximal matching can be computed in time, where denotes the number of applicants, the number of edges and the maximum rank of an…
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