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Experimental Evaluation of Approximation and Heuristic Algorithms for Maximum Distance-Bounded Subgraph Problems

Author

Listed:
  • Yuichi Asahiro

    (Kyushu Sangyo University)

  • Tomohiro Kubo

    (Kyushu Institute of Technology)

  • Eiji Miyano

    (Kyushu Institute of Technology)

Abstract

In this paper, we consider two distance-based relaxed variants of the maximum clique problem (Max Clique), named Maxd-Clique and Maxd-Club for positive integers d. Max 1-Clique and Max 1-Club cannot be efficiently approximated within a factor of $$n^{1-\varepsilon }$$ n 1 - ε for any real $$\varepsilon > 0$$ ε > 0 unless $${{{\mathcal {P}}}} = {{\mathcal {NP}}}$$ P = NP , since they are identical to Max Clique (Håstad in Acta Math 182(1):105–142, 1999; Zuckerman in Theory Comput 3:103–128, 2007). In addition, it is $${{\mathcal {NP}}}$$ NP -hard to approximate Maxd-Clique and Maxd-Club to within a factor of $$n^{1/2 - \varepsilon }$$ n 1 / 2 - ε for any fixed integer $$d\ge 2$$ d ≥ 2 and any real $$\varepsilon > 0$$ ε > 0 (Asahiro et al. in Approximating maximum diameter-bounded subgraphs. In: Proc of LATIN 2010, Springer, pp 615–626, 2010; Asahiro et al. in Optimal approximation algorithms for maximum distance-bounded subgraph problems. In: Proc of COCOA, Springer, pp 586–600, 2015). As for approximability of Maxd-Clique and Maxd-Club, a polynomial-time algorithm, called ReFindStar $$_d$$ d , that achieves an optimal approximation ratio of $$O(n^{1/2})$$ O ( n 1 / 2 ) for Maxd-Clique and Maxd-Club was designed for any integer $$d\ge 2$$ d ≥ 2 in Asahiro et al. (2015, Algorithmica 80(6):1834–1856, 2018). Moreover, a simpler algorithm, called ByFindStar $$_d$$ d , was proposed and it was shown in Asahiro et al. (2010, 2018) that although the approximation ratio of ByFindStar $$_d$$ d is much worse for any odd $$d\ge 3$$ d ≥ 3 , its time complexity is better than ReFindStar $$_d$$ d . In this paper, we implement those approximation algorithms and evaluate their quality empirically for random graphs. The experimental results show that (1) ReFindStar $$_d$$ d can find larger d-clubs (d-cliques) than ByFindStar $$_d$$ d for odd d, (2) the size of d-clubs (d-cliques) output by ByFindStar $$_d$$ d is the same as ones by ReFindStar $$_d$$ d for even d, and (3) ByFindStar $$_d$$ d can find the same size of d-clubs (d-cliques) much faster than ReFindStar $$_d$$ d . Furthermore, we propose and implement two new heuristics, Hclub $$_d$$ d for Maxd-Club and Hclique $$_d$$ d for Maxd-Clique. Then, we present the experimental evaluation of the solution size of ReFindStar $$_d$$ d , Hclub $$_d$$ d , Hclique $$_d$$ d and previously known heuristic algorithms for random graphs and Erdős collaboration graphs.

Suggested Citation

  • Yuichi Asahiro & Tomohiro Kubo & Eiji Miyano, 2019. "Experimental Evaluation of Approximation and Heuristic Algorithms for Maximum Distance-Bounded Subgraph Problems," The Review of Socionetwork Strategies, Springer, vol. 13(2), pages 143-161, October.
  • Handle: RePEc:spr:trosos:v:13:y:2019:i:2:d:10.1007_s12626-019-00036-2
    DOI: 10.1007/s12626-019-00036-2
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    References listed on IDEAS

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    1. Evgeny Maslov & Mikhail Batsyn & Panos Pardalos, 2014. "Speeding up branch and bound algorithms for solving the maximum clique problem," Journal of Global Optimization, Springer, vol. 59(1), pages 1-21, May.
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    3. Shahram Shahinpour & Sergiy Butenko, 2013. "Algorithms for the maximum k-club problem in graphs," Journal of Combinatorial Optimization, Springer, vol. 26(3), pages 520-554, October.
    4. R. Luce, 1950. "Connectivity and generalized cliques in sociometric group structure," Psychometrika, Springer;The Psychometric Society, vol. 15(2), pages 169-190, June.
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