Abstract
Many real applications involve optimisation problems where more than one objective has to be optimised at the same time. One of these kinds of problems is graph partitioning, that appears in applications such as VLSI design, data-mining, efficient disc storage of databases, etc. The problem of graph partitioning consists of dividing a graph into a given number of balanced and non-overlapping partitions while the cuts are minimised. Although different algorithms to solve this problem have been proposed, since this is an NP-complete problem, to get more efficient algorithms for increasing complex graphs still remains as an open question. In this paper, we present a new multilevel algorithm including a hybrid heuristic that is applied along the searching process. We also provide experimental results to demonstrate the efficiency of the new algorithm and compare our approach with other previously proposed efficient algorithms.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Alpert, C.J., and Kahng, A., Recent Developments in Netlist Partitioning: A Survey. Integration: the VLSI Journal, 19/ 1–2 (1995) 1–81.
Banerjee, P.: Parallel Algorithms for VLSI Computer Aided Design. Prentice Hall, Englewoods Cliffs, NJ, 1994.
Gil, C.; Ortega, J., and Montoya, M.G., Parallel VLSI Test in a Shared Memory Multiprocessors. Concurrency: Practice and Experience, 12/5 (2000) 311–326.
Klenke, R.H., Williams, R.D., and Aylor, J.H., Parallel-Processing Techniques for Automatic Test Pattern Generation, IEEE Computer, (1992) 71–84.
Gil, C. and Ortega, J., A Parallel Test Pattern Generator based on Reed-Muller Spectrum, Euromicro Workshop on Parallel and Distributed Processing, IEEE (1997) 199–204.
Mobasher, B., Jain, N., Han, E.H., Srivastava J. Web mining: Pattern discovery from world wide web transactions. Technical Report TR-96-050, Department of computer science, University of Minnesota, Minneapolis, 1996.
Shekhar S. and DLiu D.R.. Partitioning similarity graphs: A framework for declustering problems.Information Systems Journal, 21/4, (1996)
Garey, M.R., and Johnson, D.S, Computers and Intractability: A Guide to the Theory of NP-Completeness, W.H. Freeman & Company. San Francisco, 1979.
Kernighan, B.W., and Lin, S., An Efficient Heuristic Procedure for Partitioning Graphics, The Bell Sys. Tech. Journal, (1970) 291–307.
Fiduccia, C., and Mattheyses, R., A Linear Time Heuristic for Improving Network Partitions, In Proc. 19th IEEE Design Automation Conference, (1982) 175–181.
Gilbert, J., Miller, G., and Teng, S., Geometric Mesh Partitioning: Implementation and Experiments, In Proceedings of International Parallel Processing Symposium, (1995).
Karypis, G. and Kumar V.: Multilevel K-way Partitioning Scheme for Irregular Graphs. Journal of Parallel and Distributed Computing, 48/1 (1998) 96–129.
Cong, J., and Smith, M., A Parallel Bottom-up Clustering Algorithm with Applications to Circuit Partitioning in VLSI Design, In Proc. ACM/IEEE Design Automation Conference, (1993) 755–760.
Schloegel, K., Karypis, G.; and Kumar, V., Graph Partitioning for High Performance Scientific Simulations, CRPC Parallel Computing Handbook, Morgan Kaufmann2000.
Reeves, C.R., GeneticAlgorithms, in: C.R. Reeves (eds.), Modern Heuristic Techniques for Combinatorial Problems, Blackwell, London, 1993, 151–196.
Soper, A.J., Walshaw, C., and Cross, M., A Combined Evolutionary Search and Multilevel Optimisation Approach to Graph Partitioning, Mathematics Research Report 00/IM/58, University of Greenwich, 2000.
Gil, C., Ortega, J., Montoya, M.G., and Banos R., A Mixed Heuristic for Circuit Partitioning. Computational Optimization and Applications Journal. 23/3 (2002) 321–340.
Dowsland, K.A, Simulated Annealing, in: C.R. Reeves (eds.), Modern Heuristic Techniques for Combinatorial Problems, Blackwell, London, 1993, 20–69.
Glover, F., and Laguna, M., Tabu Search, in: C.R. Reeves (eds.), Modern Heuristic Techniques for Combinatorial Problems, Blackwell, London, 1993, 70–150.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Baños, R., Gil, C., Ortega, J., Montoya, F.G. (2003). Multilevel Heuristic Algorithm for Graph Partitioning. In: Cagnoni, S., et al. Applications of Evolutionary Computing. EvoWorkshops 2003. Lecture Notes in Computer Science, vol 2611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36605-9_14
Download citation
DOI: https://doi.org/10.1007/3-540-36605-9_14
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00976-4
Online ISBN: 978-3-540-36605-8
eBook Packages: Springer Book Archive