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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/4915

Title: Parallel Approximation Algorithms for Maximum Weighted Matching in General Graphs
Authors: Uehara, Ryuhei
Chen, Zhi-Zhong
Keywords: Graph algorithm
maximum weighted matching
approximation algorithm
parallel algorithm
Issue Date: 2000
Publisher: Springer
Magazine name: Lecture Notes in Computer Science
Volume: 1872
Start page: 84
End page: 98
DOI: 10.1007/3-540-44929-9_7
Abstract: The problem of computing a matching of maximum weight in a given edge-weighted graph is not known to be P-hard or in RNC. This paper presents four parallel approximation algorithms for this problem. The first is an RNC-approximation scheme, i.e., an RNC algorithm that computes a matching of weight at least 1 - ε times the maximum for any given constant ε > 0. The second one is an NC approximation algorithm achieving an approximation ratio of 1/(2+ε) for any fixed ε > 0. The third and fourth algorithms only need to know the total order of weights, so they are useful when the edge weights require a large amount of memories to represent. The third one is an NC approximation algorithm that finds a matching of weight at least 2/(3Δ+2) times the maximum, where Δ is the maximum degree of the graph. The fourth one is an RNC algorithm that finds a matching of weight at least 1/(2Δ+4) times the maximum on average, and runs in Ο(log Δ) time, not depending on the size of the graph.
Rights: This is the author-created version of Springer, Ryuhei Uehara and Zhi-Zhong Chen, Lecture Notes in Computer Science, 1872, 2000, 84-98. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/3-540-44929-9_7
URI: http://hdl.handle.net/10119/4915
Material Type: author
Appears in Collections:b10-1. 雑誌掲載論文 (Journal Articles)

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