Multiplicative auction algorithm for approximate maximum weight bipartite matching

We present an auction algorithm using multiplicative instead of constant weight updates to compute a ( 1 - ε ) -approximate maximum weight matching (MWM) in a bipartite graph with n vertices and m edges in time O ( m ε - 1 ) , beating the running time of the fastest known approximation algorithm of...

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Bibliographic Details
Published in:Mathematical programming Vol. 210; no. 1; pp. 881 - 894
Main Authors: Zheng, Da Wei, Henzinger, Monika
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2025
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ISSN:0025-5610, 1436-4646
Online Access:Get full text
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Summary:We present an auction algorithm using multiplicative instead of constant weight updates to compute a ( 1 - ε ) -approximate maximum weight matching (MWM) in a bipartite graph with n vertices and m edges in time O ( m ε - 1 ) , beating the running time of the fastest known approximation algorithm of Duan and Pettie [JACM ’14] that runs in O ( m ε - 1 log ε - 1 ) . Our algorithm is very simple and it can be extended to give a dynamic data structure that maintains a ( 1 - ε ) -approximate maximum weight matching under (1) one-sided vertex deletions (with incident edges) and (2) one-sided vertex insertions (with incident edges sorted by weight) to the other side. The total time time used is O ( m ε - 1 ) , where m is the sum of the number of initially existing and inserted edges.
ISSN:0025-5610
1436-4646
DOI:10.1007/s10107-024-02066-3