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Mathematical Problems in Engineering
Volume 2015, Article ID 238529, 10 pages
http://dx.doi.org/10.1155/2015/238529
Research Article

Moving Clusters within a Memetic Algorithm for Graph Partitioning

1Technical Laboratory, Atto Research, 225-18 Pangyoyeok-ro, Bundang-gu, Seongnam-si, Gyeonggi-do 463-400, Republic of Korea
2Department of Computer Science & Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 139-701, Republic of Korea
3Department of Computer Engineering, College of Information Technology, Gachon University, 1342 Seongnamdaero, Sujeong-gu, Seongnam-si, Gyeonggi-do 461-701, Republic of Korea

Received 23 September 2014; Accepted 7 January 2015

Academic Editor: John Gunnar Carlsson

Copyright © 2015 Inwook Hwang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Most memetic algorithms (MAs) for graph partitioning reduce the cut size of partitions using iterative improvement. But this local process considers one vertex at a time and fails to move clusters between subsets when the movement of any single vertex increases cut size, even though moving the whole cluster would reduce it. A new heuristic identifies clusters from the population of locally optimized random partitions that must anyway be created to seed the MA, and as the MA runs it makes beneficial cluster moves. Results on standard benchmark graphs show significant reductions in cut size, in some cases improving on the best result in the literature.