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Computing Minimum-Weight Perfect Matchings (1998)
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| Venue: | INFORMS Journal on Computing |
| Citations: | 98 - 2 self |
BibTeX
@ARTICLE{Cook98computingminimum-weight,
author = {William Cook and André Rohe},
title = {Computing Minimum-Weight Perfect Matchings},
journal = {INFORMS Journal on Computing},
year = {1998},
volume = {11},
pages = {138--148}
}
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Abstract
We make several observations on the implementation of Edmonds' blossom algorithm for solving minimum-weight perfect-matching problems and we present computational results for geometric problem instances ranging in size from 1,000 nodes up to 5,000,000 nodes. A key feature in our implementation is the use of multiple search trees with an individual dual-change " for each tree. As a benchmark of the algorithm's performance, solving a 100,000 node geometric instance on a 200 Mhz Pentium-Pro computer takes approximately 3 minutes. A perfect matching in a graph G is a subset of edges such that each node in G is met by exactly one edge in the subset. Given a real weight c e for each edge e of G, the minimumweight perfect-matching problem is to find a perfect matching M of minimum weight P (c e : e 2 M ). One of the fundamental results in combinatorial optimization is the polynomialtime blossom algorithm for computing minimum-weight perfect matchings by Edmonds [22, 23]. This algori...
Keyphrases
minimum-weight perfect matchings minimum weight mhz pentium-pro computer minimum-weight perfect-matching problem computational result individual dual-change polynomialtime blossom algorithm perfect matching key feature node geometric instance minimumweight perfect-matching problem real weight geometric problem instance combinatorial optimization multiple search tree blossom algorithm fundamental result several observation
