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On finding \(k\)-cliques in \(k\)-partite graphs. (English) Zbl 1276.90061

Summary: A branch-and-bound algorithm for finding all cliques of size \(k\) in a \(k\)-partite graph is proposed that improves the method of T. Grünert et al. [Comput. Oper. Res. 29, No. 1, 13–31 (2002; Zbl 1032.90034)]. The new algorithm uses bit-vectors, or bitsets, as the main data structure in bit-parallel operations. Bitsets enable a new form of data representation that improves branching and backtracking of the branch-and-bound procedure. Numerical studies on randomly generated instances of \(k\)-partite graphs demonstrate the competitiveness of the developed method.

MSC:

90C27 Combinatorial optimization
90C57 Polyhedral combinatorics, branch-and-bound, branch-and-cut

Citations:

Zbl 1032.90034
Full Text: DOI

References:

[1] Bomze, I.M., Budinich, M., Pardalos, P.M., Pelillo, M.: The maximum clique problem. In: Handbook of Combinatorial Optimization, p. 1–74. Kluwer, Dordrecht (1999) · Zbl 1253.90188
[2] Grabowski S., Fredriksson K.: Bit-parallel string matching under hamming distance in $${{O(n\(\backslash\)lceil m/w \(\backslash\)rceil) O(n\(\backslash\)lceil m/w \(\backslash\)rceil)}}$$ worst case time. Inf. Process. Lett. 105(5), 182–187 (2008) · Zbl 1184.68209 · doi:10.1016/j.ipl.2007.08.021
[3] Grunert T., Irnich S., Zimmermann H.J., Schneider M., Wulfhorst B.: Finding all k-cliques in k-partite graphs, an application in textile engineering. Comput. Oper. Res. 29(1), 13–31 (2002) · Zbl 1032.90034 · doi:10.1016/S0305-0548(00)00053-8
[4] Hyyrö H.: Bit-parallel approximate string matching algorithms with transposition. J. Discrete Algorithms 3(2–4), 215–229 (2005) · Zbl 1101.68504 · doi:10.1016/j.jda.2004.08.006
[5] Hyyrö H., Navarro G.: Bit-parallel witnesses and their applications to approximate string matching. Algorithmica 41(3), 203–231 (2004) · Zbl 1069.68115 · doi:10.1007/s00453-004-1108-z
[6] Krokhmal P., Grundel D., Pardalos P.: Asymptotic behavior of the expected optimal value of the multidimensional assignment problem. Math. Progr. 109(2–3), 525–551 (2007) · Zbl 1147.90033 · doi:10.1007/s10107-006-0036-x
[7] Krokhmal, P.A., Pardalos, P.M.: Limiting optimal values and convergence rates in some combinatorial optimization problems on hypergraph matchings. (2011, submitted)
[8] Leiserson, C.E., Prokop, H., Randall, K.H.: Using de Bruijn sequences to index a 1 in a computer word. Working paper. http://supertech.csail.mit.edu/papers/debruijn.ps (1998)
[9] Liu, Q., Chen, Y.: High functional coherence in k-partite protein cliques of protein interaction networks. In: Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, pp. 111–117 (2009)
[10] Luce R.D.: Connectivity and generalized cliques in sociometric group structure. Psychometrika 15(2), 169–190 (1950) · doi:10.1007/BF02289199
[11] Mirghorbani, M., Krokhmal P., Pasiliao E.L.: Computational studies of randomized multidimensional assignment problems. In: Sorokin, A., Thai, M.T., Pardalos, P.M. (eds.) Dynamics of Information Systems. Springer, Berlin (2012, in press) · Zbl 1268.90066
[12] Peters, M.: CLICK: Clustering categorical data using k-partite maximal cliques. In: IEEE International Conference on Data Engineering (2005)
[13] San Segundo P., Rodríguez-Losada D., Jiminez A.: An exact bit-parallel algorithm for the maximum clique problem. Comput. Oper. Res. 38(2), 571–581 (2011) · Zbl 1231.90369 · doi:10.1016/j.cor.2010.07.019
[14] Segundo, P., Tapia, C., Puente, J., Rodrguez-Losada, D.: A new exact bit-parallel algorithm for sat. In: ICTAI (2)’08, pp. 59–65 (2008)
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