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Article . 1994 . Peer-reviewed
License: Wiley Online Library User Agreement
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Local bipartite turán graphs and graph partitioning

Local bipartite Turán graphs and graph partitioning
Authors: Jon Lee 0001; Jennifer Ryan;

Local bipartite turán graphs and graph partitioning

Abstract

AbstractMotivated by the NP‐hard problem of finding a minimum‐weight balanced bipartition of an edge‐weighted complete graph, we studied the class of graphs having the same degrees as bipartite Turán graphs. In particular, we established a maximal set of linear equations satisfied by the counts of the possible incidences of 3‐ and 4‐cycles on such graphs. This leads to extremal results that we exploit in a heuristic for the partitioning problem, as well as in the computation of a Lagrangian bound. Preliminary computational results with the heuristic appear to be quite promising. Further results are established linking various adjacency concepts and measures of nonbipartiteness for such graphs. We also demonstrate the potential power of the Lagrangian bound via a family of examples. © 1994 by John Wiley & Sons, Inc.

Keywords

Lagrangian bound, heuristic, measures of nonbipartiteness, Programming involving graphs or networks, bipartite Turán graphs, minimum-weight balanced bipartition

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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