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Advances on Strictly \(\varDelta \)-Modular IPs

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Integer Programming and Combinatorial Optimization (IPCO 2023)

Abstract

There has been significant work recently on integer programs (IPs) \(\min \{c^\top x :Ax\le b,\,x\in \mathbb {Z}^n\}\) with a constraint marix A with bounded subdeterminants. This is motivated by a well-known conjecture claiming that, for any constant \(\varDelta \in \mathbb {Z}_{>0}\), \(\varDelta \)-modular IPs are efficiently solvable, which are IPs where the constraint matrix \(A\in \mathbb {Z}^{m\times n}\) has full column rank and all \(n\times n\) minors of A are within \(\{-\varDelta , \dots , \varDelta \}\). Previous progress on this question, in particular for \(\varDelta =2\), relies on algorithms that solve an important special case, namely strictly \(\varDelta \)-modular IPs, which further restrict the \(n\times n\) minors of A to be within \(\{-\varDelta , 0, \varDelta \}\). Even for \(\varDelta =2\), such problems include well-known combinatorial optimization problems like the minimum odd/even cut problem. The conjecture remains open even for strictly \(\varDelta \)-modular IPs. Prior advances were restricted to prime \(\varDelta \), which allows for employing strong number-theoretic results.

In this work, we make first progress beyond the prime case by presenting techniques not relying on such strong number-theoretic prime results. In particular, our approach implies that there is a randomized algorithm to check feasibility of strictly \(\varDelta \)-modular IPs in strongly polynomial time if \(\varDelta \le 4\).

Funded through the Swiss National Science Foundation grants 200021_184622 and P500PT_206742, the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 817750), and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXZ-2047/1 – 390685813.

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Notes

  1. 1.

    A weaker variant of the conjecture claims efficient solvability of IPs with totally \(\varDelta \)-modular constraint matrices, where all subdeterminants are bounded by \(\varDelta \) in absolute value. The conjecture involving \(\varDelta \)-modular matrices implies the weaker variant. Indeed, an IP \(\min \{c^\top x :Ax \le b, x\in \mathbb {Z}^n\}\) with a totally \(\varDelta \)-modular constraint matrix can be reformulated as \(\min \{c^\top (x^+-x^-) :A(x^+-x^-)\le b, x^+, x^- \in \mathbb {Z}_{\ge 0}^n\}\). It is not hard to see that the constraint matrix of the new LP remains totally \(\varDelta \)-modular; moreover, it has full column rank because of the non-negativity constraints.

  2. 2.

    To capture an MCCTU problem as a strictly \(\varDelta \)-modular IP, replace each congruency constraint \(\gamma _i^\top x \equiv r_i\pmod {m_i}\) by an equality constraint \(\gamma _i^\top x + m_i y_i = r\) with \(y_i\in \mathbb {Z}\). The corresponding constraint matrix is strictly \(\varDelta \)-modular for \(\varDelta =\prod _{i=1}^q m_i\).

  3. 3.

    In fact, the proof in [24] claims a reduction to a submodular minimization problem, but shows the stronger one presented here.

  4. 4.

    We recall that a lattice \(\mathcal {L}\subseteq 2^N\) is a set family such that for any \(A,B\in \mathcal {L}\), we have \(A\cap B, A\cup B\in \mathcal {L}\). We assume such a lattice to be given by a compact encoding in a directed acyclic graph H on the vertex set N such that \(X\subseteq N\) is an element of the lattice if and only if \(\delta _H^-(X)=\emptyset \) (cf. [20, Section 10.3]). Here, as usual, in a digraph \(G=(V,A)\) and for \(X\subseteq V\), we denote by \(\delta ^+(X)\) and \(\delta ^-(X)\) the arcs in A leaving and entering X, respectively. Moreover, we write \(\delta ^\pm (v){:}{=}\delta ^\pm (\{v\})\) for \(v\in V\).

  5. 5.

    For simplicity, we use a notion of a 3-sum that allows one or both of \(ef^\top \) and \(gh^\top \) to be zero matrices. Typically, those cases would be called 2- and 1-sums, respectively.

References

  1. Aprile, M., Fiorini, S.: Regular matroids have polynomial extension complexity. Math. Oper. Res. 47(1), 540–559 (2021). https://doi.org/10.1287/moor.2021.1137

    Article  MathSciNet  MATH  Google Scholar 

  2. Artmann, S., Eisenbrand, F., Glanzer, C., Oertel, T., Vempala, S., Weismantel, R.: A note on non-degenerate integer programs with small sub-determinants. Oper. Res. Lett. 44(5), 635–639 (2016). https://doi.org/10.1016/j.orl.2016.07.004

    Article  MathSciNet  MATH  Google Scholar 

  3. Artmann, S., Weismantel, R., and Zenklusen, R.: A Strongly Polynomial Algorithm for Bimodular Integer Linear Programming. In: Proceedings of the 49th Annual ACM Symposium on Theory of Computing (STOC ’17), pp. 1206–1219, Montreal (2017). https://doi.org/10.1145/3055399.3055473

  4. Averkov, G., Schymura, M.: On the Maximal Number of Columns of a \(\varDelta \) - modular Matrix. In: Proceedings of the 23rd International Conference on Integer Programming and Combinatorial Optimization (IPCO ’22), pp. 29–42, Eidhoven (2022). https://doi.org/10.1007/978-3-031-06901-7_3

  5. Barahona, F., Conforti, M.: A construction for binary matroids. Discret. Math. 66(3), 213–218 (1987). https://doi.org/10.1016/0012-365X(87)90097-5

    Article  MathSciNet  MATH  Google Scholar 

  6. Bonifas, N., Di Summa, M., Eisenbrand, F., Hähnle, N., Niemeier, M.: On Sub-determinants and the Diameter of Polyhedra. Discrete Comput. Geometry 52(1), 102–115 (2014). https://doi.org/10.1007/s00454-014-9601-x

    Article  MathSciNet  MATH  Google Scholar 

  7. Camerini, P.M., Galbiati, G., Maffioli, F.: Random pseudo-polynomial algorithms for exact matroid problems. J. Algorithms 13, 258–273 (1992). https://doi.org/10.1016/0196-6774(92)90018-8

    Article  MathSciNet  MATH  Google Scholar 

  8. Di Summa, M., Eisenbrand, F., Faenza, Y., Moldenhauer, C.: On Largest Volume Simplices and Sub-determinants. In: Proceedings of the 26th Annual ACMSIAM Symposium on Discrete Algorithms (SODA ’15), pp. 315–323, San Diego (2015). https://doi.org/10.1137/1.9781611973730.23

  9. Dinitz, M., Kortsarz, G.: Matroid secretary for regular and decomposable matroids. SIAM J. Comput. 43(5), 1807–1830 (2014). https://doi.org/10.1137/13094030X

    Article  MathSciNet  MATH  Google Scholar 

  10. Eisenbrand, F., Vempala, S.: Geometric random edge. Math. Program. 1, 325–339 (2016). https://doi.org/10.1007/s10107-016-1089-0

    Article  MathSciNet  MATH  Google Scholar 

  11. Fiorini, S., Joret, G., Weltge, S., and Yuditsky, Y.: Integer programs with bounded subdeterminants and two nonzeros per row. In: Proceedings of the 62nd Annual Symposium on Foundations of Computer Science (FOCS ’22), pp. 13–24 (2022). https://doi.org/10.1109/FOCS52979.2021.00011

  12. Glanzer, C., Stallknecht, I., and Weismantel, R.: On the recognition of a, b, c- modular matrices. In: Proceedings of the 22nd International Conference on Integer Programming and Combinatorial Optimization (IPCO ’21), pp. 238–251, Atlanta (2021). https://doi.org/10.1007/978-3-030-73879-2_17

  13. Glanzer, C., Weismantel, R., Zenklusen, R.: On the number of distinct rows of a matrix with bounded subdeterminants. SIAM J. Discret. Math. 32(3), 1706–1720 (2018). https://doi.org/10.1137/17M1125728

    Article  MathSciNet  MATH  Google Scholar 

  14. Goemans, M.X., Ramakrishnan, V.S.: Minimizing submodular functions over families of sets. Combinatorica 15(4), 499–513 (1995). https://doi.org/10.1007/BF01192523

    Article  MathSciNet  MATH  Google Scholar 

  15. Gribanov, D., Shumilov, I., Malyshev, D., Pardalos, P.: On \(\varDelta \)-modular integer linear problems in the canonical form and equivalent problems. J. Global Optim. (2022). https://doi.org/10.1007/s10898-022-01165-9

    Article  Google Scholar 

  16. Gribanov, D.V.: An FPTAS for the \(\varDelta \)-modular multidimensional knapsack problem. In: Proceedings of the International Conference on Mathematical Optimization Theory and Operations Research (MOTOR), pp. 79–95 (2021). https://doi.org/10.1007/978-3-030-77876-7_6

  17. Gribanov, D.V., Zolotykh, N.Y.: On lattice point counting in \(\varDelta \)-modular polyhedra. Optim. Lett. (1), 1–28 (2021). https://doi.org/10.1007/s11590-021-01744-x

  18. Gribanov, D.V., Veselov, S.I.: On integer programming with bounded determinants. Optim. Lett. 10(6), 1169–1177 (2015). https://doi.org/10.1007/s11590-015-0943-y

    Article  MathSciNet  MATH  Google Scholar 

  19. Grötschel, M., Lovász, L., Schrijver, A.: Corrigendum to our paper ‘The ellipsoid method and its consequences in combinatorial optimization’. Combinatorica 4(4), 291–295 (1984). https://doi.org/10.1007/BF02579139

    Article  MathSciNet  MATH  Google Scholar 

  20. Grötschel, M., Lovász, L., Schrijver, A.: Geometric Algorithms and Combinatorial Optimization. Springer, Cham (1993). https://doi.org/10.1007/978-3-642-78240-4

    Book  MATH  Google Scholar 

  21. Heller, I.: On linear systems with integral valued solutions. Pac. J. Math. 7(3), 1351–1364 (1957). https://doi.org/10.2140/pjm.1957.7.1351

    Article  MathSciNet  MATH  Google Scholar 

  22. Lee, J., Paat, J., Stallknecht, I., Xu, L.: Improving proximity bounds using sparsity. In: Baïou, M., Gendron, B., Günlük, O., Mahjoub, A.R. (eds.) ISCO 2020. LNCS, vol. 12176, pp. 115–127. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-53262-8_10

    Chapter  Google Scholar 

  23. Lee, J., Paat, J., Stallknecht, I., Xu, L.: Polynomial upper bounds on the number of differing columns of \(\varDelta \)-modular integer programs. Math. Oper. Res. (2022). https://doi.org/10.1287/moor.2022.1339

    Article  Google Scholar 

  24. Nägele, M., Santiago, R., Zenklusen, R.: Congruency-constrained TU problems beyond the bimodular case. In: Proceedings of the 33rd Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2022), pp. 2743–2790 (2022). https://doi.org/10.1137/1.9781611977073.108

  25. Nägele, M., Sudakov, B., Zenklusen, R.: Submodular minimization under congruency constraints. Combinatorica 39(6), 1351–1386 (2019). https://doi.org/10.1007/s00493-019-3900-1

    Article  MathSciNet  MATH  Google Scholar 

  26. Nägele, M., Zenklusen, R.: A new contraction technique with applications to congruency-constrained cuts. Math. Program. (6), 455–481 (2020). https://doi.org/10.1007/s10107-020-01498-x

  27. Nikolov, A.: Randomized rounding for the largest simplex problem. In: Proceedings of the 47th Annual ACM Symposium on Theory of Computing (STOC 2015), pp. 861–870, Portland (2015). https://doi.org/10.1145/2746539.2746628

  28. Paat, J., Schlöter, M., Weismantel, R.: The integrality number of an integer program. Math. Program. (6), 1–21 (2021). https://doi.org/10.1007/s10107-021-01651-0

  29. Padberg, M.W., Rao, M.R.: Odd minimum cut-sets and b-matchings. Math. Oper. Res. 7(1), 67–80 (1982). https://doi.org/10.1287/moor.7.1.67

    Article  MathSciNet  MATH  Google Scholar 

  30. Schrijver, A.: Theory of Linear and Integer Programming. Wiley, New York (1998)

    Google Scholar 

  31. Seymour, P.D.: Decomposition of regular matroids. J. Comb. Theory, Ser. B 28(3), 305–359 (1980). https://doi.org/10.1016/0095-8956(80)90075-1

    Article  MathSciNet  MATH  Google Scholar 

  32. Tardos, É.: A strongly polynomial algorithm to solve combinatorial linear programs. Oper. Res. 34(2), 250–256 (1986). https://doi.org/10.1287/opre.34.2.25

    Article  MathSciNet  MATH  Google Scholar 

  33. Veselov, S.I., Chirkov, A.J.: Integer program with bimodular matrix. Discret. Optim. 6(2), 220–222 (2009). https://doi.org/10.1016/j.disopt.2008.12.002

    Article  MathSciNet  MATH  Google Scholar 

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Nägele, M., Nöbel, C., Santiago, R., Zenklusen, R. (2023). Advances on Strictly \(\varDelta \)-Modular IPs. In: Del Pia, A., Kaibel, V. (eds) Integer Programming and Combinatorial Optimization. IPCO 2023. Lecture Notes in Computer Science, vol 13904. Springer, Cham. https://doi.org/10.1007/978-3-031-32726-1_28

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  • DOI: https://doi.org/10.1007/978-3-031-32726-1_28

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