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Parameterized Complexity of d-Hitting Set with Quotas

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SOFSEM 2021: Theory and Practice of Computer Science (SOFSEM 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12607))

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Abstract

In this paper we study a variant of the classic d -Hitting Set problem with lower and upper capacity constraints, say A and B, respectively. The input to the problem consists of a universe U, a set family, \(\mathscr {S} \), of sets over U, where each set in the family is of size at most d, a non-negative integer k; and additionally two functions \(\alpha :\mathscr {S} \rightarrow \{1,\ldots ,A\}\) and \(\beta :\mathscr {S} \rightarrow \{1,\ldots ,B\}\). The goal is to decide if there exists a hitting set of size at most k such that for every set S in the family \(\mathscr {S} \), the solution contains at least \(\alpha (S)\) elements and at most \(\beta (S)\) elements from S. We call this the \((A, B)\)-Multi d-Hitting Set problem. We study the problem in the realm of parameterized complexity. We show that \((A, B)\)-Multi d-Hitting Set can be solved in \(\mathcal {O}^{\star }(d^{k}) \) time. For the special case when \(d=3\) and \(d=4\), we have an improved bound of \(\mathcal {O}^\star (2.2738^k)\) and \(\mathcal {O}^\star (3.562^{k})\), respectively. The former matches the running time of the classical 3-Hitting Set problem. Furthermore, we show that if we do not have an upper bound constraint and the lower bound constraint is same for all the sets in the family, say \(A>1\), then the problem can be solved even faster than d-Hitting Set.

We next investigate some graph-theoretic problems which can be thought of as an implicit d-Hitting Set problem. In particular, we study \((A, B)\)-Multi Vertex Cover and \((A, B)\)-Multi Feedback Vertex Set in Tournaments. In \((A, B)\)-Multi Vertex Cover, we are given a graph G and a non-negative integer k, the goal is to find a subset \(S\subseteq V(G)\) of size at most k such that for every edge in G, S contains at least A and at most B of its endpoints. Analogously, we can define \((A, B)\)-Multi Feedback Vertex Set in Tournaments. We show that unlike Vertex Cover, which is same as \((1, 2)\)-Multi Vertex Cover, \((1, 1)\)-Multi Vertex Cover is polynomial-time solvable. Furthermore, unlike Feedback Vertex Set in Tournaments, \((A, B)\)-Multi Feedback Vertex Set in Tournaments can be solved in polynomial time.

Sushmita Gupta was supported by SERB-Starting Research Grant (SRG/2019/001870).

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Notes

  1. 1.

    \(\mathcal {O}^{\star }()\) hides factors that are polynomial in the input size.

References

  1. Abu-Khzam, F.N.: A kernelization algorithm for d-hitting set. J. Comput. Syst. Sci. 76(7), 524–531 (2010)

    Article  MathSciNet  Google Scholar 

  2. B-Jensen, J., Gutin, G.: Digraphs: Theory, Algorithms and Applications (2001)

    Google Scholar 

  3. Banerjee, S., Mathew, R., Panolan, F.: ‘target set selection’ on graphs of bounded vertex cover number (2018)

    Google Scholar 

  4. Bannach, M., Skambath, M., Tantau, T.: Kernelizing the hitting set problem in linear sequential and constant parallel time. In: 17th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2020) (2020)

    Google Scholar 

  5. Bannach, M., Tantau, T.: Computing hitting set kernels by ac 0-circuits. Theor. Comput. Syst. 1–26 (2019)

    Google Scholar 

  6. Barman, S., Fawzi, O., Ghoshal, S., Gürpınar, E.: Tight approximation bounds for maximum multi-coverage. In: Bienstock, D., Zambelli, G. (eds.) IPCO 2020. LNCS, vol. 12125, pp. 66–77. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-45771-6_6

    Chapter  Google Scholar 

  7. Berman, P., DasGupta, B., Sontag, E.: Randomized approximation algorithms for set multicover problems with applications to reverse engineering of protein and gene networks. Discrete Appl. Math. 155(6–7), 733–749 (2007)

    Article  MathSciNet  Google Scholar 

  8. van Bevern, R., Smirnov, P.V.: Optimal-size problem kernels for \( d \)-hitting set in linear time and space. arXiv preprint arXiv:2003.04578 (2020)

  9. Camion, P.: Chemins et circuits hamiltoniens des graphes complets. Comptes rendus hebdomadaires des séances de l’Académie des sciences 249(21), 2151–2152 (1959)

    MathSciNet  MATH  Google Scholar 

  10. Cygan, M., et al.: Parameterized Algorithms. Springer, Berlin (2015)

    Book  Google Scholar 

  11. De Kleer, J., Mackworth, A.K., Reiter, R.: Characterizing diagnoses and systems. Artif. Intell. 56(2–3), 197–222 (1992)

    Article  MathSciNet  Google Scholar 

  12. Downey, R.G., Fellows, M.R.: Fundamentals of Parameterized Complexity, vol. 4. Springer, Berlin (2013)

    Book  Google Scholar 

  13. El Ouali, M., Fohlin, H., Srivastav, A.: A randomised approximation algorithm for the hitting set problem. Theor. Comput. Sci. 555, 23–34 (2014)

    Article  MathSciNet  Google Scholar 

  14. Fomin, F.V., Gaspers, S., Lokshtanov, D., Saurabh, S.: Exact algorithms via monotone local search. J. ACM (JACM) 66(2), 1–23 (2019)

    Article  MathSciNet  Google Scholar 

  15. Fomin, F.V., Lokshtanov, D., Saurabh, S., Zehavi, M.: Kernelization: Theory of Parameterized Preprocessing. Cambridge University Press, Cambridge (2019)

    MATH  Google Scholar 

  16. Garey, M.R., Johnson, D.S.: Computers and Intractability, vol. 174 (1979)

    Google Scholar 

  17. Haus, U.U., Klamt, S., Stephen, T.: Computing knock-out strategies in metabolic networks. J. Comput. Biol. 15(3), 259–268 (2008)

    Article  MathSciNet  Google Scholar 

  18. Hvidsten, T.R., Lægreid, A., Komorowski, J.: Learning rule-based models of biological process from gene expression time profiles using gene ontology. Bioinformatics 19(9), 1116–1123 (2003)

    Article  Google Scholar 

  19. Jain, P., Kanesh, L., Misra, P.: Conflict free version of covering problems on graphs: Classical and parameterized. Theory Comput. Syst. 64(6), 1067–1093 (2020)

    Article  MathSciNet  Google Scholar 

  20. Kutzkov, I., Scheder, D.: Computing minimum directed feedback vertex set in \(o(1.9977^n)\). abs/1007.1166 (2010)

    Google Scholar 

  21. Mellor, D., Prieto, E., Mathieson, L., Moscato, P.: A kernelisation approach for multiple d-hitting set and its application in optimal multi-drug therapeutic combinations. PLoS One 5(10), e13055 (2010)

    Article  Google Scholar 

  22. Misra, N., Narayanaswamy, N., Raman, V., Shankar, B.S.: Solving min ones 2-sat as fast as vertex cover. Theor. Comput. Sci. 506, 115–121 (2013)

    Article  MathSciNet  Google Scholar 

  23. Moon, J.W.: Topics on Tournaments in Graph Theory. Courier Dover Publications, United States (2015)

    Google Scholar 

  24. Niedermeier, R., Rossmanith, P.: An efficient fixed-parameter algorithm for 3-hitting set. J. Discrete Algorithms 1(1), 89–102 (2003)

    Article  MathSciNet  Google Scholar 

  25. Shi, L., Cai, X.: An exact fast algorithm for minimum hitting set. In: 2010 Third International Joint Conference on Computational Science and Optimization, vol. 1, pp. 64–67 (2010)

    Google Scholar 

  26. Speckenmeyer, E.: On feedback problems in digraphs. In: International Workshop on Graph-Theoretic Concepts in Computer Science, pp. 218–231 (1989)

    Google Scholar 

  27. Vazquez, A.: Optimal drug combinations and minimal hitting sets. BMC Syst. Biol. 3(1), 81 (2009)

    Article  Google Scholar 

  28. Fernandez de la Vega, W., Paschos, V.T., Saad, R.: Average case analysis of a greedy algorithm for the minimum hitting set problem. In: Simon, I. (ed.) LATIN 1992. LNCS, vol. 583, pp. 130–138. Springer, Heidelberg (1992). https://doi.org/10.1007/BFb0023824

    Chapter  Google Scholar 

  29. Wahlström, M.: Algorithms, measures and upper bounds for satisfiability and related problems. Ph.D. thesis, Doctoral dissertation, Department of Computer and Information Science, Linköpings universitet (2007)

    Google Scholar 

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Gupta, S., Jain, P., Petety, A., Singh, S. (2021). Parameterized Complexity of d-Hitting Set with Quotas. In: Bureš, T., et al. SOFSEM 2021: Theory and Practice of Computer Science. SOFSEM 2021. Lecture Notes in Computer Science(), vol 12607. Springer, Cham. https://doi.org/10.1007/978-3-030-67731-2_21

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  • DOI: https://doi.org/10.1007/978-3-030-67731-2_21

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