Knapsack with Vertex Cover, Set Cover, and Hitting Set

Authors Palash Dey , Ashlesha Hota , Sudeshna Kolay , Sipra Singh



PDF
Thumbnail PDF

File

LIPIcs.ISAAC.2024.27.pdf
  • Filesize: 0.82 MB
  • 17 pages

Document Identifiers

Author Details

Palash Dey
  • Indian Institute of Technology Kharagpur, India
Ashlesha Hota
  • Indian Institute of Technology Kharagpur, India
Sudeshna Kolay
  • Indian Institute of Technology Kharagpur, India
Sipra Singh
  • Indian Institute of Technology Kharagpur, India

Cite As Get BibTex

Palash Dey, Ashlesha Hota, Sudeshna Kolay, and Sipra Singh. Knapsack with Vertex Cover, Set Cover, and Hitting Set. In 35th International Symposium on Algorithms and Computation (ISAAC 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 322, pp. 27:1-27:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/LIPIcs.ISAAC.2024.27

Abstract

In the Vertex Cover Knapsack problem, we are given an undirected graph G = (V, E), with weights (w(u))_{u ∈ V} and values (𝛂(u))_{u ∈ V} of the vertices, the size s of the knapsack, a target value p, and the goal is to compute if there exists a vertex cover U ⊆ V with total weight at most s, and total value at least p. This problem simultaneously generalizes the classical vertex cover and knapsack problems. We show that this problem is strongly NP-complete. However, it admits a pseudo-polynomial time algorithm for trees. In fact, we show that there is an algorithm that runs in time O (2^tw ⋅ n ⋅ min) where tw is the treewidth of G. Moreover, we can compute a (1-ε)- approximate solution for maximizing the value of the solution given the knapsack size as input in time O (2^tw ⋅ poly(n,1/ε,log(∑_{v ∈ V} 𝛂(v)))) and a (1+ε)-approximate solution to minimize the size of the solution given a target value as input, in time O (2^tw ⋅ poly(n,1/ε,log(∑_{v ∈ V} w(v)))) for every ε > 0. Restricting our attention to polynomial-time algorithms only, we then consider polynomial-time algorithms and present a 2 factor polynomial-time approximation algorithm for this problem for minimizing the total weight of the solution, which is optimal up to additive o(1) assuming Unique Games Conjecture (UGC). On the other hand, we show that there is no ρ factor polynomial-time approximation algorithm for maximizing the total value of the solution given a knapsack size for any ρ > 1 unless 𝖯 = NP.
Furthermore, we show similar results for the variants of the above problem when the solution U needs to be a minimal vertex cover, minimum vertex cover, and vertex cover of size at most k for some input integer k. Then, we consider set families (equivalently hypergraphs) and study the variants of the above problem when the solution needs to be a set cover and hitting set. We show that there are H_d and f factor polynomial-time approximation algorithms for Set Cover Knapsack where d is the maximum cardinality of any set and f is the maximum number of sets in the family where any element can belongs in the input for minimizing the weight of the knapsack given a target value, and a d factor polynomial-time approximation algorithm for d-Hitting Set Knapsack which are optimal up to additive o(1) assuming UGC. On the other hand, we show that there is no ρ factor polynomial-time approximation algorithm for maximizing the total value of the solution given a knapsack size for any ρ > 1 unless 𝖯 = NP for both Set Cover Knapsack and d-Hitting Set Knapsack.

Subject Classification

ACM Subject Classification
  • Theory of computation → Approximation algorithms analysis
Keywords
  • Knapsack
  • vertex cover
  • minimal vertex cover
  • minimum vertex cover
  • hitting set
  • set cover
  • algorithm
  • approximation algorithm
  • parameterized complexity

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. Andrea Bettinelli, Valentina Cacchiani, and Enrico Malaguti. A branch-and-bound algorithm for the knapsack problem with conflict graph. INFORMS J. Comput., 29(3):457-473, 2017. URL: https://doi.org/10.1287/ijoc.2016.0742.
  2. Flavia Bonomo and Diego de Estrada. On the thinness and proper thinness of a graph. Discret. Appl. Math., 261:78-92, 2019. URL: https://doi.org/10.1016/J.DAM.2018.03.072.
  3. Nicolas Boria, Federico Della Croce, and Vangelis Th. Paschos. On the max min vertex cover problem. Discret. Appl. Math., 196:62-71, 2015. URL: https://doi.org/10.1016/J.DAM.2014.06.001.
  4. Nicolas Boria, Federico Della Croce, and Vangelis Th Paschos. On the max min vertex cover problem. Discrete Applied Mathematics, 196:62-71, 2015. URL: https://doi.org/10.1016/J.DAM.2014.06.001.
  5. Stefano Coniglio, Fabio Furini, and Pablo San Segundo. A new combinatorial branch-and-bound algorithm for the knapsack problem with conflicts. Eur. J. Oper. Res., 289(2):435-455, 2021. URL: https://doi.org/10.1016/j.ejor.2020.07.023.
  6. Marek Cygan, Fedor V Fomin, Lukasz Kowalik, Daniel Lokshtanov, Dániel Marx, Marcin Pilipczuk, Michał Pilipczuk, and Saket Saurabh. Parameterized algorithms, volume 5. Springer, 2015. URL: https://doi.org/10.1007/978-3-319-21275-3.
  7. Peter Damaschke. Parameterized algorithms for double hypergraph dualization with rank limitation and maximum minimal vertex cover. Discrete Optimization, 8(1):18-24, 2011. URL: https://doi.org/10.1016/J.DISOPT.2010.02.006.
  8. Palash Dey, Ashlesha Hota, Sudeshna Kolay, and Sipra Singh. Knapsack with vertex cover, set cover, and hitting set, 2024. URL: https://arxiv.org/abs/arXiv:2406.01057.
  9. Palash Dey, Sudeshna Kolay, and Sipra Singh. Knapsack: Connectedness, path, and shortest-path. In Latin American Symposium on Theoretical Informatics, pages 162-176. Springer, 2024. URL: https://doi.org/10.1007/978-3-031-55601-2_11.
  10. Uriel Feige. A threshold of ln n for approximating set cover. J. ACM, 45(4):634-652, 1998. URL: https://doi.org/10.1145/285055.285059.
  11. Herbert Fleischner, Gert Sabidussi, and Vladimir I. Sarvanov. Maximum independent sets in 3- and 4-regular hamiltonian graphs. Discret. Math., 310(20):2742-2749, 2010. URL: https://doi.org/10.1016/j.disc.2010.05.028.
  12. M. R. Garey and David S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman, 1979. Google Scholar
  13. Steffen Goebbels, Frank Gurski, and Dominique Komander. The knapsack problem with special neighbor constraints. Math. Methods Oper. Res., 95(1):1-34, 2022. URL: https://doi.org/10.1007/s00186-021-00767-5.
  14. Frank Gurski and Carolin Rehs. Solutions for the knapsack problem with conflict and forcing graphs of bounded clique-width. Math. Methods Oper. Res., 89(3):411-432, 2019. URL: https://doi.org/10.1007/s00186-019-00664-y.
  15. Xin Han, Kazuo Iwama, Rolf Klein, and Andrzej Lingas. Approximating the maximum independent set and minimum vertex coloring on box graphs. In Ming-Yang Kao and Xiang-Yang Li, editors, Algorithmic Aspects in Information and Management, Third International Conference, AAIM 2007, Portland, OR, USA, June 6-8, 2007, Proceedings, volume 4508 of Lecture Notes in Computer Science, pages 337-345. Springer, 2007. URL: https://doi.org/10.1007/978-3-540-72870-2_32.
  16. David G. Harris and N. S. Narayanaswamy. A faster algorithm for vertex cover parameterized by solution size. In Olaf Beyersdorff, Mamadou Moustapha Kanté, Orna Kupferman, and Daniel Lokshtanov, editors, 41st International Symposium on Theoretical Aspects of Computer Science, STACS 2024, March 12-14, 2024, Clermont-Ferrand, France, volume 289 of LIPIcs, pages 40:1-40:18. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024. URL: https://doi.org/10.4230/LIPICS.STACS.2024.40.
  17. Stephan Held, William J. Cook, and Edward C. Sewell. Maximum-weight stable sets and safe lower bounds for graph coloring. Math. Program. Comput., 4(4):363-381, 2012. URL: https://doi.org/10.1007/s12532-012-0042-3.
  18. Mhand Hifi and Mustapha Michrafy. A reactive local search-based algorithm for the disjunctively constrained knapsack problem. Journal of the Operational Research Society, 57(6):718-726, 2006. URL: https://doi.org/10.1057/PALGRAVE.JORS.2602046.
  19. Mhand Hifi and Mustapha Michrafy. Reduction strategies and exact algorithms for the disjunctively constrained knapsack problem. Computers & operations research, 34(9):2657-2673, 2007. URL: https://doi.org/10.1016/J.COR.2005.10.004.
  20. Subhash Khot and Oded Regev. Vertex cover might be hard to approximate to within 2-epsilon. J. Comput. Syst. Sci., 74(3):335-349, 2008. URL: https://doi.org/10.1016/J.JCSS.2007.06.019.
  21. Thiago Alcântara Luiz, Haroldo Gambini Santos, and Eduardo Uchoa. Cover by disjoint cliques cuts for the knapsack problem with conflicting items. Oper. Res. Lett., 49(6):844-850, 2021. URL: https://doi.org/10.1016/j.orl.2021.10.001.
  22. Carlo Mannino, Gianpaolo Oriolo, Federico Ricci-Tersenghi, and L. Sunil Chandran. The stable set problem and the thinness of a graph. Oper. Res. Lett., 35(1):1-9, 2007. URL: https://doi.org/10.1016/J.ORL.2006.01.009.
  23. Ulrich Pferschy and Joachim Schauer. The knapsack problem with conflict graphs. J. Graph Algorithms Appl., 13(2):233-249, 2009. URL: https://doi.org/10.7155/jgaa.00186.
  24. Ulrich Pferschy and Joachim Schauer. Approximation of knapsack problems with conflict and forcing graphs. J. Comb. Optim., 33(4):1300-1323, 2017. URL: https://doi.org/10.1007/s10878-016-0035-7.
  25. Vijay V Vazirani. Approximation algorithms, volume 1. Springer, 2001. Google Scholar
  26. Douglas Brent West et al. Introduction to graph theory, volume 2. Prentice hall Upper Saddle River, 2001. Google Scholar
  27. David P Williamson and David B Shmoys. The design of approximation algorithms. Cambridge university press, 2011. Google Scholar
  28. Takeo Yamada, Seija Kataoka, and Kohtaro Watanabe. Heuristic and exact algorithms for the disjunctively constrained knapsack problem. Information Processing Society of Japan Journal, 43(9), 2002. Google Scholar
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail