Heuristic to reduce the complexity of complete bipartite graphs to accelerate the search for maximum weighted matchings with small error
| dc.creator | Etzold, Daniel | |
| dc.date | 2003-06-23 | |
| dc.date.accessioned | 2026-07-07T03:19:57Z | |
| dc.date.available | 2026-07-07T03:19:57Z | |
| dc.description | A maximum weighted matching for bipartite graphs $G=(A \cup B,E)$ can be found by using the algorithm of Edmonds and Karp with a Fibonacci Heap and a modified Dijkstra in $O(nm + n^2 \log{n})$ time where n is the number of nodes and m the number of edges. For the case that $|A|=|B|$ the number of edges is $n^2$ and therefore the complexity is $O(n^3)$. In this paper we want to present a simple heuristic method to reduce the number of edges of complete bipartite graphs $G=(A \cup B,E)$ with $|A|=|B|$ such that $m = n\log{n}$ and therefore the complexity of such that $m = n\log{n}$ and therefore the complexity of $O(n^2 \log{n})$. The weights of all edges in G must be uniformly distributed in [0,1]. | |
| dc.description | 5 pages, 2 figures | |
| dc.identifier | https://arxiv.org/abs/cs/0306123 | |
| dc.identifier | http://arxiv.org/abs/cs/0306123 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/31669 | |
| dc.subject | Data Structures and Algorithms | |
| dc.subject | G.2.2 | |
| dc.title | Heuristic to reduce the complexity of complete bipartite graphs to accelerate the search for maximum weighted matchings with small error | |
| dc.type | text |