An iterative mincut heuristic for partitioning networks is presented whose worst case computation time, per pass, grows linearly with the size of the network. In practice, only a very small number of passes are typically needed, leading to a fast approximation algorithm for mincut partitioning. To deal with cells of various sizes, the algorithm progresses by moving one cell at a time between the blocks of the partition while maintaining a desired balance based on the size of the blocks rather than the number of cells per block. Efficient data structures are used to avoid unnecessary searching for the best cell to move and to minimize unnecessary updating of cells affected by each move.
Description
Welcome to IEEE Xplore 2.0: A Linear-Time Heuristic for Improving Network Partitions
%0 Journal Article
%1 Fiduccia82linearMinCut
%A Fiduccia, C.M.
%A Mattheyses, R.M.
%D 1982
%J Design Automation, 1982. 19th Conference on
%K 82 Fiduccia clustering graph heuristic linear min-cut
%P 175-181
%T A Linear-Time Heuristic for Improving Network Partitions
%X An iterative mincut heuristic for partitioning networks is presented whose worst case computation time, per pass, grows linearly with the size of the network. In practice, only a very small number of passes are typically needed, leading to a fast approximation algorithm for mincut partitioning. To deal with cells of various sizes, the algorithm progresses by moving one cell at a time between the blocks of the partition while maintaining a desired balance based on the size of the blocks rather than the number of cells per block. Efficient data structures are used to avoid unnecessary searching for the best cell to move and to minimize unnecessary updating of cells affected by each move.
@article{Fiduccia82linearMinCut,
abstract = { An iterative mincut heuristic for partitioning networks is presented whose worst case computation time, per pass, grows linearly with the size of the network. In practice, only a very small number of passes are typically needed, leading to a fast approximation algorithm for mincut partitioning. To deal with cells of various sizes, the algorithm progresses by moving one cell at a time between the blocks of the partition while maintaining a desired balance based on the size of the blocks rather than the number of cells per block. Efficient data structures are used to avoid unnecessary searching for the best cell to move and to minimize unnecessary updating of cells affected by each move.},
added-at = {2008-10-18T19:21:30.000+0200},
author = {Fiduccia, C.M. and Mattheyses, R.M.},
biburl = {https://www.bibsonomy.org/bibtex/2f310eb1147cd6e29c5cd055ec3d15f9e/lee_peck},
description = {Welcome to IEEE Xplore 2.0: A Linear-Time Heuristic for Improving Network Partitions},
interhash = {b3891a7c2ec1871a79946049a0576236},
intrahash = {f310eb1147cd6e29c5cd055ec3d15f9e},
issn = {0146-7123},
journal = {Design Automation, 1982. 19th Conference on},
keywords = {82 Fiduccia clustering graph heuristic linear min-cut},
month = {June},
pages = { 175-181},
timestamp = {2009-02-02T16:43:45.000+0100},
title = {A Linear-Time Heuristic for Improving Network Partitions},
year = 1982
}