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Speeding up branch and bound algorithms for solving the maximum clique problem

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In this paper we consider two branch and bound algorithms for the maximum clique problem which demonstrate the best performance on DIMACS instances among the existing methods. These algorithms are MCS algorithm by Tomita et al. (2010) and MAXSAT algorithm by Li and Quan (2010a, b). We suggest a general approach which allows us to speed up considerably these branch and bound algorithms on hard instances. The idea is to apply a powerful heuristic for obtaining an initial solution of high quality. This solution is then used to prune branches in the main branch and bound algorithm. For this purpose we apply ILS heuristic by Andrade et al. (J Heuristics 18(4):525–547, 2012). The best results are obtained for p_hat1000-3 instance and gen instances with up to 11,000 times speedup.

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Acknowledgments

The authors would like to thank professor Mauricio Resende and his co-authors for the source code of their powerful ILS heuristic. We are also thankful to Chu-Min Li and Zhe Quan for the source code of their efficient MAXSAT algorithm. The authors are supported by LATNA Laboratory, National Research University Higher School of Economics (NRU HSE), Russian Federation government grant, ag. 11.G34.31.0057. Mikhail Batsyn is supported by Federal Grant-in-Aid Program “Research and development on priority directions of development of the scientific-technological complex of Russia for 2007–2013” (Governmental Contract No. 14.514.11.4065).

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Maslov, E., Batsyn, M. & Pardalos, P.M. Speeding up branch and bound algorithms for solving the maximum clique problem. J Glob Optim 59, 1–21 (2014). https://doi.org/10.1007/s10898-013-0075-9

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