Abstract
Partitioning is a fundamental problem in diverse fields of study such as VLSI design, parallel processing, data mining and task scheduling. The min-cut bipartitioning problem is a fundamental graph partitioning problem and is NP-Complete. In this paper, we present an effective multi-level refinement algorithm based on swarm intelligence for bisecting graph. The success of our algorithm relies on exploiting both the swarm intelligence theory with a boundary refinement policy. Our experimental evaluations on 18 different benchmark graphs show that our algorithm produces high quality solutions compared with those produced by MeTiS that is a state-of-the-art partitioner in the literature.
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References
Alpert, C.J., Kahng, A.B.: Recent directions in netlist partitioning. Integration, the VLSI Journal 19, 1–81 (1995)
Hendrickson, B., Leland, R.: An improved spectral graph partitioning algorithm for mapping parallel computations. SIAM Journal on Scientific Computing 16, 452–469 (1995)
Ding, C., He, X., Zha, H., Gu, M., Simon, H.: A Min-Max cut algorithm for graph partitioning and data clustering. In: Proc. IEEE Conf. Data Mining, pp. 107–114. IEEE Computer Society Press, Los Alamitos (2001)
Khannat, G., Vydyanathant, N.: A hypergraph partitioning based approach for scheduling of tasks with batch-shared I/O. In: IEEE International Symposium on Cluster Computing and the Grid, pp. 792–799 (2005)
Bui, T., Leland, C.: Finding good approximate vertex and edge partitions is NP-hard. Information Processing Letters 42, 153–159 (1992)
Kernighan, B.W., Lin, S.: An efficient heuristic procedure for partitioning graphs. Bell System Technical Journal 49, 291–307 (1970)
Fiduccia, C., Mattheyses, R.: A linear-time heuristics for improving network partitions. In: Proc. 19th Design Automation Conf., pp. 175–181 (1982)
Tao, L., Zhao, Y.C., Thulasiraman, K., Swamy, M.N.S.: Simulated annealing and tabu search algorithms for multiway graph partition. Journal of Circuits, Systems and Computers, 159–185 (1992)
Żola, J., Wyrzykowski, R.: Application of genetic algorithm for mesh partitioning. In: Proc. Workshop on Parallel Numerics, pp. 209–217 (2000)
Bahreininejad, A., Topping, B.H.V., Khan, A.I.: Finite element mesh partitioning using neural networks. Advances in Engineering Software, pp. 103–115 (1996)
Leng, M., Yu, S., Chen, Y.: An effective refinement algorithm based on multi-level paradigm for graph bipartitioning. In: The IFIP TC5 International Conference on Knowledge Enterprise. IFIP Series, pp. 294–303. Springer, Heidelberg (2006)
Leng, M., Yu, S.: An effective multi-level algorithm for bisecting graph. In: Li, X., Zaïane, O.R., Li, Z. (eds.) ADMA 2006. LNCS (LNAI), vol. 4093, pp. 493–500. Springer, Heidelberg (2006)
Karypis, G., Kumar, V.: MeTiS 4.0: Unstructured graphs partitioning and sparse matrix ordering system. Technical Report, Department of Computer Science, University of Minnesota (1998)
Karypis, G., Kumar, V.: A fast and highly quality multilevel scheme for partitioning irregular graphs. SIAM Journal on Scientific Computing 20, 359–392 (1998)
Selvakkumaran, N., Karypis, G.: Multi-objective hypergraph partitioning algorithms for cut and maximum subdomain degree minimization. IEEE Trans. Computer Aided Design 25, 504–517 (2006)
Koros̃ec, P., S̃ilc, J., Robic̃, B.: Solving the mesh-partitioning problem with an ant-colony algorithm. Parallel Computing, 785–801 (2004)
Alpert, C.J.: The ISPD98 circuit benchmark suite. In: Proc. Intel Symposium of Physical Design, pp. 80–85 (1998)
Millonas, M.: Swarms, phase transitions, and collective intelligence. In: Langton, C. (ed.) Artificial Life III, Addison-Wesley, Reading (1994)
Dorigo, M., Maniezzo, V., Colorni, A.: Ant system: Optimization by a colony of cooperating agents. IEEE Trans. on SMC, 29–41 (1996)
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proc. IEEE Conf. Neural Networks IV, pp. 1942–1948. IEEE Computer Society Press, Los Alamitos (1995)
Langham, A.E., Grant, P.W.: Using competing ant colonies to solve k-way partitioning problems with foraging and raiding strategies. In: Floreano, D., Mondada, F. (eds.) ECAL 1999. LNCS, vol. 1674, pp. 621–625. Springer, Heidelberg (1999)
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Sun, L., Leng, M. (2007). An Effective Refinement Algorithm Based on Swarm Intelligence for Graph Bipartitioning. In: Chen, B., Paterson, M., Zhang, G. (eds) Combinatorics, Algorithms, Probabilistic and Experimental Methodologies. ESCAPE 2007. Lecture Notes in Computer Science, vol 4614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74450-4_6
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DOI: https://doi.org/10.1007/978-3-540-74450-4_6
Publisher Name: Springer, Berlin, Heidelberg
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