7 research outputs found
Rank Maximal Matchings -- Structure and Algorithms
Let G = (A U P, E) be a bipartite graph where A denotes a set of agents, P
denotes a set of posts and ranks on the edges denote preferences of the agents
over posts. A matching M in G is rank-maximal if it matches the maximum number
of applicants to their top-rank post, subject to this, the maximum number of
applicants to their second rank post and so on.
In this paper, we develop a switching graph characterization of rank-maximal
matchings, which is a useful tool that encodes all rank-maximal matchings in an
instance. The characterization leads to simple and efficient algorithms for
several interesting problems. In particular, we give an efficient algorithm to
compute the set of rank-maximal pairs in an instance. We show that the problem
of counting the number of rank-maximal matchings is #P-Complete and also give
an FPRAS for the problem. Finally, we consider the problem of deciding whether
a rank-maximal matching is popular among all the rank-maximal matchings in a
given instance, and give an efficient algorithm for the problem
Manipulation Strategies for the Rank Maximal Matching Problem
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 edge in an optimal solution.
A central authority matches applicants to posts. It does so using one of the
rank-maximal matchings. Since there may be more than one rank- maximal matching
of , we assume that the central authority chooses any one of them randomly.
Let be a manipulative applicant, who knows the preference lists of all
the other applicants and wants to falsify his preference list so that he has a
chance of getting better posts than if he were truthful. In the first problem
addressed in this paper the manipulative applicant wants to ensure that
he is never matched to any post worse than the most preferred among those of
rank greater than one and obtainable when he is truthful. In the second problem
the manipulator wants to construct such a preference list that the worst post
he can become matched to by the central authority is best possible or in other
words, wants to minimize the maximal rank of a post he can become matched
to
Favoring Eagerness for Remaining Items: Designing Efficient, Fair, and Strategyproof Mechanisms
In the assignment problem, the goal is to assign indivisible items to agents
who have ordinal preferences, efficiently and fairly, in a strategyproof
manner. In practice, first-choice maximality, i.e., assigning a maximal number
of agents their top items, is often identified as an important efficiency
criterion and measure of agents' satisfaction. In this paper, we propose a
natural and intuitive efficiency property,
favoring-eagerness-for-remaining-items (FERI), which requires that each item is
allocated to an agent who ranks it highest among remaining items, thereby
implying first-choice maximality. Using FERI as a heuristic, we design
mechanisms that satisfy ex-post or ex-ante variants of FERI together with
combinations of other desirable properties of efficiency (Pareto-efficiency),
fairness (strong equal treatment of equals and sd-weak-envy-freeness), and
strategyproofness (sd-weak-strategyproofness). We also explore the limits of
FERI mechanisms in providing stronger efficiency, fairness, or
strategyproofness guarantees through impossibility results