Stable matchings in metric spaces

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Abstract/Contents

Abstract
Suppose each of $n$ men and $n$ women is located at a point in a metric space. A woman ranks the men in order of their distance to her from closest to farthest, breaking ties at random. The men rank the women similarly. An interesting problem is to use these ranking lists and find a stable matching in the sense of Gale and Shapley. This problem formulation naturally models preferences in several real world applications; for example, dating sites, room renting/letting, ride hailing and labor markets. Two key questions that arise in this setting are: (a) When is the stable matching unique without resorting to tie breaks? (b) If $X$ is the distance between a randomly chosen stable pair, what is the distribution of $X$ and what is $E(X)$? These questions address conditions under which it is possible to find a unique (stable) partner, and the quality of the stable matching in terms of the rank or the proximity of the partner. We study dating sites and ride hailing as prototypical examples of stable matchings in discrete and continuous metric spaces, respectively. In the dating site model, each man/woman is assigned to a point on the $k$-dimensional hypercube based on their answers to a set of $k$ questions with binary answers ({\it e.g.}\ , like/dislike). We consider two different metrics on the hypercube: Hamming and Weighted Hamming (in which the answers to some questions carry more weight). Under both metrics, there are exponentially many stable matchings when $k = \lfloor\log n\rfloor$. There is a unique stable matching, with high probability, under the Hamming distance when $k = \Omega(n^6)$, and under the Weighted Hamming distance when $k > (2+\epsilon) \log n$ for some $\epsilon> 0$. In the ride hailing model, passengers and cabs are modeled as points on the line and matched based on Euclidean distance (a proxy for pickup time). Assuming the locations of the passengers and cabs are independent Poisson processes of different intensities, we derive bounds on the distribution of $X$ in terms of busy periods at a last-come-first-served preemptive-resume (LCFS-PR) queue. We also study the college admission problem where the goal is to find a stable matching between students and colleges. In our analysis, we consider a utility-based model for the preference lists of colleges and students. We derive sufficient conditions on the utility functions to have a unique stable matching. We also model the interview process in the college admission problem, and show that if conducting interviews are costly, in certain circumstances we may see over-qualification of applicants.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date ©2018
Publication date 2018; 2018
Issuance monographic
Language English

Creators/Contributors

Author Abadi, Hossein Karkeh
Degree supervisor Prabhakar, Balaji, 1967-
Thesis advisor Prabhakar, Balaji, 1967-
Thesis advisor Akbarpour, Mohammad
Thesis advisor Tse, David
Degree committee member Akbarpour, Mohammad
Degree committee member Tse, David
Associated with Stanford University, Department of Electrical Engineering.

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Hossein Karkeh Abadi.
Note Submitted to the Department of Electrical Engineering.
Thesis Thesis Ph.D. Stanford University 2018.
Location electronic resource

Access conditions

Copyright
© 2018 by Hossein Karkeh Abadi
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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