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by Joe Marks, Wheeler Ruml, Stuart M. Shieber, J. Thomas Ngo
http://www.eecs.harvard.edu/cgi-bin/ruml/wr-log?papers/alex98.ps.gz
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Abstract:
We present a new heuristic algorithm for graph bisection, based on an implicit notion of clustering. We describe how the heuristic can be combined with stochastic search procedures and a postprocess application of the Kernighan-Lin algorithm. In a series of time-equated comparisons with large-sample runs of pure Kernighan-Lin, the new algorithm demonstrates significant superiority in terms of the best bisections found. 1
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