FPT Inapproximability of Directed Cut and Connectivity Problems

Authors Rajesh Chitnis, Andreas Emil Feldmann



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Rajesh Chitnis
  • School of Computer Science, University of Birmingham, UK
Andreas Emil Feldmann
  • Charles University, Czechia

Acknowledgements

We thank Pasin Manurangsi for helpful discussions.

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Rajesh Chitnis and Andreas Emil Feldmann. FPT Inapproximability of Directed Cut and Connectivity Problems. In 14th International Symposium on Parameterized and Exact Computation (IPEC 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 148, pp. 8:1-8:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019) https://doi.org/10.4230/LIPIcs.IPEC.2019.8

Abstract

Cut problems and connectivity problems on digraphs are two well-studied classes of problems from the viewpoint of parameterized complexity. After a series of papers over the last decade, we now have (almost) tight bounds for the running time of several standard variants of these problems parameterized by two parameters: the number k of terminals and the size p of the solution. When there is evidence of FPT intractability, then the next natural alternative is to consider FPT approximations. In this paper, we show two types of results for directed cut and connectivity problems, building on existing results from the literature: first is to circumvent the hardness results for these problems by designing FPT approximation algorithms, or alternatively strengthen the existing hardness results by creating "gap-instances" under stronger hypotheses such as the (Gap-)Exponential Time Hypothesis (ETH). Formally, we show the following results: 

Cutting paths between a set of terminal pairs, i.e., Directed Multicut: Pilipczuk and Wahlstrom [TOCT '18] showed that Directed Multicut is W[1]-hard when parameterized by p if k=4. We complement this by showing the following two results: 
- Directed Multicut has a k/2-approximation in 2^{O(p^2)}* n^{O(1)} time (i.e., a 2-approximation if k=4), 
- Under Gap-ETH, Directed Multicut does not admit an (59/58-epsilon)-approximation in f(p)* n^{O(1)} time, for any computable function f, even if k=4. 

Connecting a set of terminal pairs, i.e., Directed Steiner Network (DSN): The DSN problem on general graphs is known to be W[1]-hard parameterized by p+k due to Guo et al. [SIDMA '11]. Dinur and Manurangsi [ITCS '18] further showed that there is no FPT k^{1/4-o(1)}-approximation algorithm parameterized by k, under Gap-ETH. Chitnis et al. [SODA '14] considered the restriction to special graph classes, but unfortunately this does not lead to FPT algorithms either: DSN on planar graphs is W[1]-hard parameterized by k. In this paper we consider the DSN_Planar problem which is an intermediate version: the graph is general, but we want to find a solution whose cost is at most that of an optimal planar solution (if one exists). We show the following lower bounds for DSN_Planar: 
- DSN_Planar has no (2-epsilon)-approximation in FPT time parameterized by k, under Gap-ETH. This answers in the negative a question of Chitnis et al. [ESA '18]. 
- DSN_Planar is W[1]-hard parameterized by k+p. Moreover, under ETH, there is no (1+epsilon)-approximation for DSN_Planar in f(k,p,epsilon)* n^{o(k+sqrt{p+1/epsilon})} time for any computable function f. 

Pairwise connecting a set of terminals, i.e., Strongly Connected Steiner Subgraph (SCSS): Guo et al. [SIDMA '11] showed that SCSS is W[1]-hard parameterized by p+k, while Chitnis et al. [SODA '14] showed that SCSS remains W[1]-hard parameterized by p, even if the input graph is planar. In this paper we consider the SCSS_Planar problem which is an intermediate version: the graph is general, but we want to find a solution whose cost is at most that of an optimal planar solution (if one exists). We show the following lower bounds for SCSS_Planar: 
- SCSS_Planar is W[1]-hard parameterized by k+p. Moreover, under ETH, there is no (1+epsilon)-approximation for SCSS_Planar in f(k,p,epsilon)* n^{o(sqrt{k+p+1/epsilon})} time for any computable function f. 
 Previously, the only known FPT approximation results for SCSS applied to general graphs parameterized by k: a 2-approximation by Chitnis et al. [IPEC '13], and a matching (2-epsilon)-hardness under Gap-ETH by Chitnis et al. [ESA '18].

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Graph algorithms
Keywords
  • Directed graphs
  • cuts
  • connectivity
  • Steiner problems
  • FPT inapproximability

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References

  1. Amit Agarwal, Noga Alon, and Moses Charikar. Improved approximation for directed cut problems. In STOC, pages 671-680, 2007. URL: https://doi.org/10.1145/1250790.1250888.
  2. Benny Applebaum. Exponentially-Hard Gap-CSP and Local PRG via Local Hardcore Functions. In FOCS 2017, pages 836-847, 2017. URL: https://doi.org/10.1109/FOCS.2017.82.
  3. Sanjeev Arora, László Babai, Jacques Stern, and Z. Sweedyk. The Hardness of Approximate Optima in Lattices, Codes, and Systems of Linear Equations. J. Comput. Syst. Sci., 54(2):317-331, 1997. URL: https://doi.org/10.1006/jcss.1997.1472.
  4. Piotr Berman, Arnab Bhattacharyya, Konstantin Makarychev, Sofya Raskhodnikova, and Grigory Yaroslavtsev. Approximation algorithms for spanner problems and Directed Steiner Forest. Information and Computation, 222:93-107, 2013. Google Scholar
  5. Parinya Chalermsook, Marek Cygan, Guy Kortsarz, Bundit Laekhanukit, Pasin Manurangsi, Danupon Nanongkai, and Luca Trevisan. From Gap-ETH to FPT-Inapproximability: Clique, Dominating Set, and More. In FOCS, pages 743-754, 2017. URL: https://doi.org/10.1109/FOCS.2017.74.
  6. Moses Charikar, Chandra Chekuri, To-Yat Cheung, Zuo Dai, Ashish Goel, Sudipto Guha, and Ming Li. Approximation Algorithms for Directed Steiner Problems. J. Algorithms, 33(1):73-91, 1999. URL: https://doi.org/10.1006/jagm.1999.1042.
  7. Chandra Chekuri, Guy Even, Anupam Gupta, and Danny Segev. Set connectivity problems in undirected graphs and the directed Steiner network problem. ACM Transactions on Algorithms, 7(2):18, 2011. Google Scholar
  8. Chandra Chekuri and Vivek Madan. Approximating Multicut and the Demand Graph. In SODA, pages 855-874, 2017. URL: https://doi.org/10.1137/1.9781611974782.54.
  9. Jianer Chen, Xiuzhen Huang, Iyad A. Kanj, and Ge Xia. Strong computational lower bounds via parameterized complexity. J. Comput. Syst. Sci., 72(8):1346-1367, 2006. Google Scholar
  10. Rajesh Chitnis and Andreas Emil Feldmann and. FPT Inapproximability of Directed Cut and Connectivity Problems. CoRR, abs/1910.01934, 2019. URL: http://arxiv.org/abs/1910.01934.
  11. Rajesh Chitnis, Andreas Emil Feldmann, and Pasin Manurangsi. Parameterized Approximation Algorithms for Bidirected Steiner Network Problems. In ESA, pages 20:1-20:16, 2018. URL: https://doi.org/10.4230/LIPIcs.ESA.2018.20.
  12. Rajesh Hemant Chitnis, Marek Cygan, Mohammad Taghi Hajiaghayi, and Dániel Marx. Directed Subset Feedback Vertex Set Is Fixed-Parameter Tractable. ACM Trans. Algorithms, 11(4):28:1-28:28, 2015. URL: https://doi.org/10.1145/2700209.
  13. Rajesh Hemant Chitnis, MohammadTaghi Hajiaghayi, and Guy Kortsarz. Fixed-Parameter and Approximation Algorithms: A New Look. In IPEC 2013, pages 110-122, 2013. URL: https://doi.org/10.1007/978-3-319-03898-8_11.
  14. Rajesh Hemant Chitnis, MohammadTaghi Hajiaghayi, and Dániel Marx. Fixed-Parameter Tractability of Directed Multiway Cut Parameterized by the Size of the Cutset. SIAM J. Comput., 42(4):1674-1696, 2013. URL: https://doi.org/10.1137/12086217X.
  15. Rajesh Hemant Chitnis, MohammadTaghi Hajiaghayi, and Dániel Marx. Tight Bounds for Planar Strongly Connected Steiner Subgraph with Fixed Number of Terminals (and Extensions). In SODA, pages 1782-1801, 2014. URL: https://doi.org/10.1137/1.9781611973402.129.
  16. Julia Chuzhoy and Sanjeev Khanna. Polynomial flow-cut gaps and hardness of directed cut problems. J. ACM, 56(2):6:1-6:28, 2009. URL: https://doi.org/10.1145/1502793.1502795.
  17. Irit Dinur. Mildly exponential reduction from gap 3SAT to polynomial-gap label-cover. Electronic Colloquium on Computational Complexity (ECCC), 23:128, 2016. Google Scholar
  18. Irit Dinur and Pasin Manurangsi. ETH-Hardness of Approximating 2-CSPs and Directed Steiner Network. In ITCS, pages 36:1-36:20, 2018. URL: https://doi.org/10.4230/LIPIcs.ITCS.2018.36.
  19. Yevgeniy Dodis and Sanjeev Khanna. Design networks with bounded pairwise distance. In STOC 1999, pages 750-759, 1999. Google Scholar
  20. Jon Feldman and Matthias Ruhl. The Directed Steiner Network Problem is Tractable for a Constant Number of Terminals. SIAM J. Comput., 36(2):543-561, 2006. URL: https://doi.org/10.1137/S0097539704441241.
  21. Moran Feldman, Guy Kortsarz, and Zeev Nutov. Improved approximation algorithms for Directed Steiner Forest. J. Comput. Syst. Sci., 78(1):279-292, 2012. URL: https://doi.org/10.1016/j.jcss.2011.05.009.
  22. Andreas Emil Feldmann and Dániel Marx. The Complexity Landscape of Fixed-Parameter Directed Steiner Network Problems. CoRR, abs/1707.06808, 2017. URL: http://arxiv.org/abs/1707.06808.
  23. Naveen Garg, Vijay V. Vazirani, and Mihalis Yannakakis. Multiway Cuts in Directed and Node Weighted Graphs. In ICALP, pages 487-498, 1994. URL: https://doi.org/10.1007/3-540-58201-0_92.
  24. Jiong Guo, Rolf Niedermeier, and Ondrej Suchý. Parameterized Complexity of Arc-Weighted Directed Steiner Problems. SIAM J. Discrete Math., 25(2):583-599, 2011. Google Scholar
  25. Eran Halperin and Robert Krauthgamer. Polylogarithmic inapproximability. STOC '03, pages 585-594, 2003. URL: https://doi.org/10.1145/780542.780628.
  26. Russell Impagliazzo and Ramamohan Paturi. On the Complexity of k-SAT. J. Comput. Syst. Sci., 62(2):367-375, 2001. Google Scholar
  27. Russell Impagliazzo, Ramamohan Paturi, and Francis Zane. Which Problems Have Strongly Exponential Complexity? J. Comput. Syst. Sci., 63(4):512-530, 2001. Google Scholar
  28. Subhash Khot. On the power of unique 2-prover 1-round games. In STOC, pages 767-775, 2002. URL: https://doi.org/10.1145/509907.510017.
  29. Guy Kortsarz and David Peleg. On Choosing a Dense Subgraph (Extended Abstract). In FOCS 1993, pages 692-701, 1993. Google Scholar
  30. Euiwoong Lee. Improved Hardness for Cut, Interdiction, and Firefighter Problems. In ICALP, pages 92:1-92:14, 2017. URL: https://doi.org/10.4230/LIPIcs.ICALP.2017.92.
  31. Daniel Lokshtanov, Dániel Marx, and Saket Saurabh. Lower bounds based on the Exponential Time Hypothesis. Bulletin of the EATCS, 105:41-72, 2011. URL: http://eatcs.org/beatcs/index.php/beatcs/article/view/92.
  32. Pasin Manurangsi and Prasad Raghavendra. A Birthday Repetition Theorem and Complexity of Approximating Dense CSPs. In ICALP, pages 78:1-78:15, 2017. Google Scholar
  33. Dániel Marx. Can You Beat Treewidth? Theory of Computing, 6(1):85-112, 2010. URL: https://doi.org/10.4086/toc.2010.v006a005.
  34. Dániel Marx and Igor Razgon. Fixed-Parameter Tractability of Multicut Parameterized by the Size of the Cutset. SIAM J. Comput., 43(2):355-388, 2014. URL: https://doi.org/10.1137/110855247.
  35. Joseph Naor and Leonid Zosin. A 2-Approximation Algorithm for the Directed Multiway Cut Problem. SIAM J. Comput., 31(2):477-482, 2001. URL: https://doi.org/10.1137/S009753979732147X.
  36. Marcin Pilipczuk and Magnus Wahlström. Directed Multicut is W[1]-hard, Even for Four Terminal Pairs. TOCT, 10(3):13:1-13:18, 2018. URL: https://doi.org/10.1145/3201775.
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