Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 60 tok/s
Gemini 2.5 Pro 50 tok/s Pro
GPT-5 Medium 22 tok/s Pro
GPT-5 High 18 tok/s Pro
GPT-4o 82 tok/s Pro
Kimi K2 197 tok/s Pro
GPT OSS 120B 458 tok/s Pro
Claude Sonnet 4.5 30 tok/s Pro
2000 character limit reached

Two-sided popular matchings in bipartite graphs with forbidden/forced elements and weights (1803.01478v2)

Published 5 Mar 2018 in cs.DM

Abstract: Two-sided popular matchings in bipartite graphs are a well-known generalization of stable matchings in the marriage setting, and they are especially relevant when preference lists are incomplete. In this case, the cardinality of a stable matching can be as small as half the size of a maximum matching. Popular matchings allow for assignments of larger size while still guaranteeing a certain fairness condition. In fact, stable matchings are popular matchings of minimum size, and a maximum size popular matching can be as large as twice the size of a(ny) stable matching in a given instance. The structure of popular matchings seems to be more complex, and currently less understood, than that of stable matchings. In this paper, we focus on three optimization problems related to popular matchings. First, we give a granular analysis of the complexity of popular matching with forbidden and forced elements problems, thus complementing results from [Cseh and Kavitha, 2016]. In particular, we show that deciding whether there exists a popular matching with (or without) two given edges is NP-Hard. This implies that finding a popular matching of maximum (resp. minimum) weight is NP-Hard and, even if all weights are nonnegative, inapproximable up to a factor 1/2 (resp. up to any factor). A decomposition theorem from [Cseh and Kavitha, 2016] can be employed to give a 1/2 approximation to the maximum weighted popular matching problem with nonnegative weights, thus completely settling the complexity of those problems.

Citations (2)

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.