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A Hybrid Approach for Exact Coloring of Massive Graphs

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Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2019)

Abstract

The graph coloring problem appears in numerous applications, yet many state-of-the-art methods are hardly applicable to real world, very large, networks. The most efficient approaches for massive graphs rely on “peeling” the graph of its low-degree vertices and focus on the maximum k-core where k is some lower bound on the chromatic number of the graph. However, unless the graphs are extremely sparse, the cores can be very large, and lower and upper bounds are often obtained using greedy heuristics.

In this paper, we introduce a combined approach using local search to find good quality solutions on massive graphs as well as locate small subgraphs with potentially large chromatic number. The subgraphs can be used to compute good lower bounds, which makes it possible to solve optimally extremely large graphs, even when they have large k-cores.

G. Katsirelos—The second author was partially supported by the french “Agence nationale de la Recherche”, project DEMOGRAPH, reference ANR-16-C40-0028.

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Notes

  1. 1.

    http://www.info.univ-angers.fr/~porumbel/graphs/.

  2. 2.

    denotes our implementation of the Dsatur heuristic.

  3. 3.

    Ties broken by overall degree.

  4. 4.

    Sources available at: https://bitbucket.org/gkatsi/minicsp.

  5. 5.

    Sources available at: https://bitbucket.org/gkatsi/gc-cdcl/src/master/.

  6. 6.

    Personnal communication with the authors.

  7. 7.

    email-Eu-core, email-EuAll, Gnutella08/09, bitcoinalpha, bitcoinotc, facebook, gplus, CollegeMsg and sx-superuser.

References

  1. Aardal, K.I., Hoesel, S.P.M.V., Koster, A.M.C.A., Mannino, C., Sassano, A.: Models and solution techniques for frequency assignment problems. Ann. Oper. Res. 153(1), 79–129 (2007)

    Article  MathSciNet  Google Scholar 

  2. Abello, J., Pardalos, P., Resende, M.G.C.: On maximum clique problems in very large graphs. In: Abello, J.M., Vitter, J.S. (eds.) External Memory Algorithms, pp. 119–130. American Mathematical Society, Boston (1999)

    Chapter  Google Scholar 

  3. Bader, D.A., Meyerhenke, H., Sanders, P., Wagner, D.: Graph partitioning and graph clustering (2012). http://www.cc.gatech.edu/dimacs10/

  4. Blöchliger, I., Zufferey, N.: A graph coloring heuristic using partial solutions and a reactive tabu scheme. Comput. Oper. Res. 35(3), 960–975 (2008)

    Article  MathSciNet  Google Scholar 

  5. Brélaz, D.: New methods to color the vertices of a graph. Commun. ACM 22(4), 251–256 (1979)

    Article  MathSciNet  Google Scholar 

  6. Chaitin, G.J., Auslander, M.A., Chandra, A.K., Cocke, J., Hopkins, M.E., Markstein, P.W.: Register allocation via coloring. Comput. Lang. 6(1), 47–57 (1981)

    Article  Google Scholar 

  7. Cornaz, D., Jost, V.: A one-to-one correspondence between colorings and stable sets. Oper. Res. Lett. 36(6), 673–676 (2008)

    Article  MathSciNet  Google Scholar 

  8. de Werra, D.: An introduction to timetabling. Eur. J. Oper. Res. 19(2), 151–162 (1985)

    Article  MathSciNet  Google Scholar 

  9. Furini, F., Gabrel, V., Ternier, I.-C.: Lower bounding techniques for DSATUR-based branch and bound. Electron. Notes Discrete Math. 52, 149–156 (2016). INOC 2015–7th International Network Optimization Conference

    Article  MathSciNet  Google Scholar 

  10. Hao, J.-K., Qinghua, W.: Improving the extraction and expansion method for large graph coloring. Discrete Appl. Math. 160(16–17), 2397–2407 (2012)

    Article  MathSciNet  Google Scholar 

  11. Hebrard, E., Katsirelos, G.: Clause learning and new bounds for graph coloring. In: Hooker, J. (ed.) CP 2018. LNCS, vol. 11008, pp. 179–194. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-98334-9_12

    Chapter  Google Scholar 

  12. Hertz, A., de Werra, D.: Using tabu search techniques for graph coloring. Computing 39(4), 345–351 (1987)

    Article  MathSciNet  Google Scholar 

  13. Johnson, D.J., Trick, M.A. (eds.): Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, Workshop, October 11–13, 1993. American Mathematical Society, Boston (1996)

    MATH  Google Scholar 

  14. Leighton, F.T.: A graph coloring algorithm for large scheduling problems. J. Res. Natl. Bur. Stand. 84, 489–506 (1979)

    Article  MathSciNet  Google Scholar 

  15. Leskovec, J., Krevl, A.: SNAP datasets: Stanford large network dataset collection (2014). http://snap.stanford.edu/data

  16. Lin, J., Cai, S., Luo, C., Su, K.: A reduction based method for coloring very large graphs. In: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, pp. 517–523 (2017)

    Google Scholar 

  17. Lovász, L.: On the Shannon capacity of a graph. IEEE Trans. Inf. Theor. 25(1), 1–7 (2006)

    Article  MathSciNet  Google Scholar 

  18. Malaguti, E., Monaci, M., Toth, P.: An exact approach for the vertex coloring problem. Discrete Optim. 8(2), 174–190 (2011)

    Article  MathSciNet  Google Scholar 

  19. Matula, D.W., Beck, L.L.: Smallest-last ordering and clustering and graph coloring algorithms. J. ACM 30(3), 417–427 (1983)

    Article  MathSciNet  Google Scholar 

  20. Mehrotra, A., Trick, M.A.: A column generation approach for graph coloring. INFORMS J. Comput. 8, 344–354 (1995)

    Article  Google Scholar 

  21. Moalic, L., Gondran, A.: Variations on memetic algorithms for graph coloring problems. CoRR, abs/1401.2184 (2014)

    Google Scholar 

  22. Mycielski, J.: Sur le coloriage des graphes. Colloq. Math. 3, 161–162 (1955)

    Article  MathSciNet  Google Scholar 

  23. Park, T., Lee, C.Y.: Application of the graph coloring algorithm to the frequency assignment problem. J. Oper. Res. Soc. Jpn. 39(2), 258–265 (1996)

    Article  MathSciNet  Google Scholar 

  24. Rossi, R.A., Ahmed, N.K.: Coloring large complex networks. CoRR, abs/1403.3448 (2014)

    Google Scholar 

  25. Schaafsma, B., Heule, M.J.H., van Maaren, H.: Dynamic symmetry breaking by simulating zykov contraction. In: Kullmann, O. (ed.) SAT 2009. LNCS, vol. 5584, pp. 223–236. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02777-2_22

    Chapter  Google Scholar 

  26. Segundo, P.S.: A new DSATUR-based algorithm for exact vertex coloring. Comput. Oper. Res. 39(7), 1724–1733 (2012)

    Article  MathSciNet  Google Scholar 

  27. Van Gelder, A.: Another look at graph coloring via propositional satisfiability. Discrete Appl. Math. 156(2), 230–243 (2008)

    Article  MathSciNet  Google Scholar 

  28. Verma, A., Buchanan, A., Butenko, S.: Solving the maximum clique and vertex coloring problems on very large sparse networks. INFORMS J. Comput. 27(1), 164–177 (2015)

    Article  Google Scholar 

  29. Walteros, J.L., Buchanan, A.: Why is maximum clique often easy in practice? Optimization Online (2018). http://www.optimization-online.org/DB_HTML/2018/07/6710.html

  30. Zhou, Z., Li, C.-M., Huang, C., Ruchu, X.: An exact algorithm with learning for the graph coloring problem. Comput. Oper. Res. 51, 282–301 (2014)

    Article  MathSciNet  Google Scholar 

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Hebrard, E., Katsirelos, G. (2019). A Hybrid Approach for Exact Coloring of Massive Graphs. In: Rousseau, LM., Stergiou, K. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2019. Lecture Notes in Computer Science(), vol 11494. Springer, Cham. https://doi.org/10.1007/978-3-030-19212-9_25

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  • DOI: https://doi.org/10.1007/978-3-030-19212-9_25

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