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A tight \(\sqrt{2}\)-approximation for linear 3-cut

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Abstract

We investigate the approximability of the linear 3-cut problem in directed graphs. The input here is a directed graph \(D=(V,E)\) with node weights and three specified terminal nodes \(s,r,t\in V\), and the goal is to find a minimum weight subset of non-terminal nodes whose removal ensures that s cannot reach r and t, and r cannot reach t. The precise approximability of linear 3-cut has been wide open until now: the best known lower bound under the unique games conjecture (UGC) was 4 / 3, while the best known upper bound was 2 using a trivial algorithm. In this work we completely close this gap: we present a \(\sqrt{2}\)-approximation algorithm and show that this factor is tight under UGC. Our contributions are twofold: (1) we analyze a natural two-step deterministic rounding scheme through the lens of a single-step randomized rounding scheme with non-trivial distributions, and (2) we construct integrality gap instances that meet the upper bound of \(\sqrt{2}\). Our gap instances can be viewed as a weighted graph sequence converging to a “graph limit structure”. We complement our results by showing connections between the linear 3-cut problem and other fundamental cut problems in directed graphs.

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Notes

  1. Node weighted k-way cut in undirected graphs has no \((2-2/k-\epsilon )\)-approximation assuming UGC [7].

  2. Reduction from Skew-\((k-1)\)-Multicut to Edge-Lin- \(k\) -Cut: Add new nodes \(s_1',\dots ,s_k'\) and infinite weight edges \(s_i'\rightarrow s_i\) for \(i \in [1,k-1]\), \(t_{i-1}\rightarrow s_i'\) for \(i \in [2,k]\) and solve the Edge-Lin- \(k\) -Cut instance with terminals \((s_1',\dots ,s_k')\). Reduction from Edge-Lin- \(k\) -Cut to Skew-\((k-1)\)-skew-multicut: Given a directed graph with terminals \((s_1,\dots ,s_k)\), add new nodes \(s_1',\dots ,s_{k-1}',t_1',\dots ,t_{k-1}'\) and infinite weight edges \(s_i'\rightarrow s_i\) for \(i \in [1,k-1]\), \(s_i\rightarrow t_{i-1}'\) for \(i \in [2,k]\) and solve the skew-multicut problem w.r.t. terminal sets \((s_1',\dots ,s_{k-1}')\), \((t_1',\dots ,t_{k-1}')\).

  3. Pick \(\theta \in (0,1)\) and set \(K_1\) to be the set of nodes which have incoming (outgoing) arcs to nodes which are within a distance \(\theta \) from the terminal(s) of interest. Since there are only polynomially many \(\theta \) values of interest, the best solution can be obtained in polynomial time.

  4. The various boundary conditions in the definition of the node weights will have to use appropriately rounded down and rounded up boundary values. We avoid this technicality in the interests of simplicity.

References

  1. Bérczi, K., Chandrasekaran, K., Király, K., Lee, E., Xu, C.: Global and fixed-terminal cuts in digraphs. In: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM). Leibniz International Proceedings in Informatics (LIPIcs), vol. 81, pp. 2:1–2:20 (2017)

  2. Bernáth, A., Pap, G.: Blocking optimal arborescences. Math. Program. 161(1), 583–601 (2017)

    MathSciNet  MATH  Google Scholar 

  3. Chekuri, C., Kamath, S., Kannan, S., Viswanath, P.: Delay-constrained unicast and the triangle-cast problem. In: IEEE International Symposium on Information Theory (ISIT), pp. 804–808 (2015)

  4. Chekuri, C., Madan, V.: Approximating multicut and the demand graph. In: Proceedings of the 28th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 855–874 (2017)

  5. Cheung, K., Cunningham, W., Tang, L.: Optimal 3-terminal cuts and linear programming. Math. Program. 106(1), 1–23 (2006)

    MathSciNet  MATH  Google Scholar 

  6. Dahlhaus, E., Johnson, D., Papadimitriou, C., Seymour, P., Yannakakis, M.: The complexity of multiterminal cuts. SIAM J. Comput. 23(4), 864–894 (1994)

    MathSciNet  MATH  Google Scholar 

  7. Ene, A., Vondrák, J., Wu, Y.: Local distribution and the symmetry gap: approximability of multiway partitioning problems. In: Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pp. 306–325 (2013)

  8. Erbacher, R., Jaeger, T., Talele, N., Teutsch, J.: Directed multicut with linearly ordered terminals (2014). Preprint https://arxiv.org/abs/1407.7498

  9. Garg, N., Vazirani, V., Yannakakis, M.: Multiway cuts in node weighted graphs. J. Algorithms 50(1), 49–61 (2004)

    MathSciNet  MATH  Google Scholar 

  10. Goemans, M., Williamson, D.: Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming. J. ACM 42(6), 1115–1145 (1995)

    MathSciNet  MATH  Google Scholar 

  11. Karger, D., Klein, P., Stein, C., Thorup, M., Young, N.: Rounding algorithms for a geometric embedding of minimum multiway cut. Math. Oper. Res. 29(3), 436–461 (2004)

    Article  MathSciNet  Google Scholar 

  12. Khot, S., Kindler, G., Mossel, E., O’Donnell, R.: Optimal inapproximability results for MAX-CUT and other 2-variable CSPs? SIAM J. Comput. 37(1), 319–357 (2007)

    MathSciNet  MATH  Google Scholar 

  13. Lee, E.: Improved hardness for cut, interdiction, and firefighter problems. In: 44th International Colloquium on Automata, Languages, and Programming (ICALP). Leibniz International Proceedings in Informatics (LIPIcs), vol. 80, pp. 92:1–92:14 (2017)

  14. Manokaran, R., Naor, J., Raghavendra, P., Schwartz, R.: SDP gaps and UGC hardness for multiway cut, 0-extension, and metric labeling. In: Proceedings of the 40th Annual ACM Symposium on Theory of Computing (STOC), pp. 11–20 (2008)

  15. Muthukumaran, D., Rueda, S., Talele, N., Vijayakumar, H., Teutsch, J., Jaeger, T.: Transforming commodity security policies to enforce Clark–Wilson integrity. In: Proceedings of the 28th Annual Computer Security Applications Conference (ACSAC), pp. 269–278 (2012)

  16. Talele, N., Teutsch, J., Jaeger, T., Erbacher, R.: Using security policies to automate placement of network intrusion prevention. In: Proceedings of the 5th International Symposium on Engineering Secure Software and Systems (ESSoS), pp. 17–32 (2013)

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Correspondence to Karthekeyan Chandrasekaran.

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An extended abstract of this work appeared in the 29th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2018).

Kristóf and Tamás are supported by the Hungarian National Research, Development and Innovation Office—NKFIH Grants K109240 and K120254 and by the ÚNKP-17-4 New National Excellence Program of the Ministry of Human Capacities.

Karthekeyan is supported by NSF CCF-1907937 and NSF CCF-1814613. Vivek is supported by NSF CCF-1319376.

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Appendix A. Necessary conditions for (2)

Appendix A. Necessary conditions for (2)

Claim

Condition (2) is satisfied by \(\xi \) if and only if the following hold for \(\zeta \):

$$\begin{aligned} \zeta \left( \frac{\sqrt{2}-1}{\sqrt{2}}\right)&=0, \end{aligned}$$
(13)
$$\begin{aligned} (1-y) \zeta (y)+\int _y^{1-y}\zeta (z)\, \mathrm {d} z&=\frac{1}{2}\quad \text {if }\frac{\sqrt{2}-1}{\sqrt{2}} \le y \le \frac{1}{2}, \end{aligned}$$
(14)
$$\begin{aligned} (1-y) \zeta (y)-\int _{1-y}^y \zeta (z)\, \mathrm {d} z&=\frac{1}{2}\quad \text {if }\frac{1}{2} \le y \le \frac{1}{\sqrt{2}}. \end{aligned}$$
(15)

Proof

The direction showing that (13)–(15) imply (2) was already shown in Claim 4. We now argue the necessity of (13), (14) and (15).

To see the necessity of (14), we consider \(a=b=y\) for \(\frac{\sqrt{2}-1}{\sqrt{2}} \le y \le \frac{1}{2}\). For this choice of a and b, condition (2) necessitates that

$$\begin{aligned} 1&= 2\int _0^1 \xi (y,z)\, \mathrm {d} z + 2 \int _y^1 \xi (z,y)\, \mathrm {d} z\\&= 2\int _0^{1-y} \xi (y,z)\, \mathrm {d} z + 2 \int _y^{1-y} \xi (z,y)\, \mathrm {d} z\\&= 2\int _0^{1-y} \zeta (y)\, \mathrm {d} z + 2 \int _{y}^{1-y} \zeta (z)\, \mathrm {d} z\\&= 2 (1-y) \zeta (y)+ 2 \int _y^{1-y}\zeta (z)\, \mathrm {d} z, \end{aligned}$$

which shows the necessity of (14). The second equation above is because \(\xi (y,z)=\xi (z,y)=0\) for \(z > 1-y\) since \(y\le 1/2\).

To see the necessity of (15), we consider \(a=y\), \(b=1-y\) for some y such that \(\frac{1}{2} \le y \le \frac{1}{\sqrt{2}}\). For this choice of a and b, condition (2) necessitates that

$$\begin{aligned} 1&=\int _0^1 \left( \xi (y,z)+\xi (1-y,z)\right) \, \mathrm {d} z + \int _y^1 \xi (z,1-y)\, \mathrm {d} z + \int _{1-y}^1 \xi (z,y)\, \mathrm {d} z \nonumber \\&= \int _0^1 \xi (y,z)\, \mathrm {d} z + \int _{0}^1 \xi (1-y,z)\, \mathrm {d} z + 0 + 0 \nonumber \\&= \int _0^{1-y} \xi (y,z)\, \mathrm {d} z + \int _{0}^y \xi (1-y,z)\, \mathrm {d} z \nonumber \\&= \int _0^{1-y} \zeta (y)\, \mathrm {d} z + \int _{0}^{y}\zeta (1-y)\, \mathrm {d} z \nonumber \\&= (1-y) \zeta (y) + y\zeta (1-y). \end{aligned}$$
(16)

We note that the bounds on y imply that \(\frac{\sqrt{2}-1}{\sqrt{2}} \le 1-y \le \frac{1}{2}\). Hence, by (14) applied to \(y':=1-y\), we obtain that

$$\begin{aligned} y \zeta (1-y) = \frac{1}{2} - \int _{1-y}^{y}\zeta (z)\, \mathrm {d} z. \end{aligned}$$
(17)

Substituting (17) in (16) and rewriting in the required form shows the necessity of (15).

To see the necessity of (13), we consider \(a=b<\frac{\sqrt{2}-1}{\sqrt{2}}\). For this choice of a and b, condition (2) necessitates that

$$\begin{aligned} 1&=2 \int _0^1 \xi (a,z)\, \mathrm {d} z + 2 \int _a^1 \xi (z,a)\, \mathrm {d} z =0 + 2 \int _a^1 \xi (z,a)\, \mathrm {d} z = 2\int _{\frac{\sqrt{2}-1}{\sqrt{2}}}^{\frac{1}{\sqrt{2}}}\zeta (z)\, \mathrm {d} z. \end{aligned}$$
(18)

Now, by (14) applied to \(y=\frac{\sqrt{2}-1}{\sqrt{2}}\), we obtain that

$$\begin{aligned} \frac{1}{2}=\frac{1}{\sqrt{2}}\zeta \left( \frac{\sqrt{2}-1}{\sqrt{2}}\right) + \int _{\frac{\sqrt{2}-1}{\sqrt{2}}}^{\frac{1}{\sqrt{2}}} \zeta (z)dz = \frac{1}{\sqrt{2}}\zeta \left( \frac{\sqrt{2}-1}{\sqrt{2}}\right) + \frac{1}{2} \end{aligned}$$

where the second equation is obtained by substituting (18). Hence, \(\zeta (\frac{\sqrt{2}-1}{\sqrt{2}})=0\), showing the necessity of (13). \(\square \)

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Bérczi, K., Chandrasekaran, K., Király, T. et al. A tight \(\sqrt{2}\)-approximation for linear 3-cut. Math. Program. 184, 411–443 (2020). https://doi.org/10.1007/s10107-019-01417-9

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