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FPT-algorithms for some problems related to integer programming

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Abstract

In this paper, we present fixed-parameter tractable algorithms for special cases of the shortest lattice vector, integer linear programming, and simplex width computation problems, when matrices included in the problems’ formulations are near square. The parameter is the maximum absolute value of the rank minors in the corresponding matrices. Additionally, we present fixed-parameter tractable algorithms with respect to the same parameter for the problems, when the matrices have no singular rank submatrices.

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References

  • Ajtai M (1996) Generating hard instances of lattice problems. In: Proceedings of 28th annual ACM symposium on the theory of computing, pp 99–108

  • Ajtai M, Kumar R, Sivakumar D (2001) A sieve algorithm for the shortest lattice vector problem. In: Proceedings of the 33rd annual ACM symposium on theory of computing, pp 601–610

  • Ajtai M, Kumar R, Sivakumar D (2002) Sampling short lattice vectors and the closest lattice vector problem. In: Proceedings of 17th IEEE annual conference on computational complexity, pp 53–57

  • Alekseev VV, Zakharova D (2011) Independent sets in the graphs with bounded minors of the extended incidence matrix. J Appl Ind Math 5:14–18

    Article  MathSciNet  Google Scholar 

  • Artmann S, Eisenbrand F, Glanzer C, Timm O, Vempala S, Weismantel R (2016) A note on non-degenerate integer programs with small subdeterminants. Oper Res Lett 44(5):635–639

    Article  MathSciNet  Google Scholar 

  • Artmann S, Weismantel R, Zenklusen R (2017) A strongly polynomial algorithm for bimodular integer linear programming. In: Proceedings of 49th annual ACM symposium on theory of computing, pp 1206–1219

  • Blömer J, Naewe S (2009) Sampling methods for shortest vectors, closest vectors and successive minima. Theor Comput Sci 410(18):1648–1665

    Article  MathSciNet  MATH  Google Scholar 

  • Bock A, Faenza Y, Moldenhauer C, Vargas R, Jacinto A (2014) Solving the stable set problem in terms of the odd cycle packing number. In: Proceedings of 34th annual conference on foundations of software technology and theoretical computer science, pp 187–198

  • Bonifas N, Di Summa M, Eisenbrand F, Hähnle N, Niemeier M (2014) On subdeterminants and the diameter of polyhedra. Discrete Computat Geom 52(1):102–115

    Article  MATH  Google Scholar 

  • Cassels JWS (1971) An introduction to the geometry of numbers, 2nd edn. Springer, Berlin

    MATH  Google Scholar 

  • Cheon JH, Lee C (2015) Approximate algorithms on lattices with small determinant. Cryptology ePrint Archive, Report 2015/461. http://eprint.iacr.org/2015/461

  • Cook W, Gerards AMH, Schrijver A, Tardos E (1986) Sensitivity theorems in integer linear programming. Math Program 34:251–264

    Article  MathSciNet  MATH  Google Scholar 

  • Cygan M, Fomin FV, Kowalik L, Lokshtanov D, Marx D, Pilipczuk M, Pilipczuk M, Saurabh S (2015) Parameterized algorithms. Springer, Berlin

    Book  MATH  Google Scholar 

  • Dadush D, Peikert C, Vempala S (2011) Enumerative algorithms for the shortest and closest lattice vector problems in any norm via M-ellipsoid coverings. In: 52nd IEEE annual symposium on foundations of computer science, pp 580–589

  • Downey RG, Fellows MR (1999) Parameterized complexity. Springer, Berlin

    Book  MATH  Google Scholar 

  • Eisenbrand F, Vempala S (2016) Geometric random edge. arXiv:1404.1568v5

  • Eisenbrand F, Hähnle N, Niemeier M (2011) Covering cubes and the closest vector problem. In: Proceedings of 27th annual symposium on computational geometry, pp 417–423

  • Fincke U, Pohst M (1983) A procedure for determining algebraic integers of given norm. Lecture Notes in Computer Science, vol 162, pp 194–202

  • Fincke U, Pohst M (1985) Improved methods for calculating vectors of short length in a lattice, including a complexity analysis. Math Comput 44(170):463–471

    Article  MathSciNet  MATH  Google Scholar 

  • Gomory RE (1965) On the relation between integer and non-integer solutions to linear programs. Proc Natl Acad Sci USA 53(2):260–265

    Article  MathSciNet  MATH  Google Scholar 

  • Gribanov DV (2013) The flatness theorem for some class of polytopes and searching an integer point. Springer Proc Math Stat 104:37–45

    Article  MATH  Google Scholar 

  • Gribanov DV, Chirkov AJ (2016) The width and integer optimization on simplices with bounded minors of the constraint matrices. Optim Lett 10(6):1179–1189

    Article  MathSciNet  MATH  Google Scholar 

  • Gribanov DV, Malyshev DS (2017) The computational complexity of three graph problems for instances with bounded minors of constraint matrices. Discrete Appl Math 227:13–20

    Article  MathSciNet  MATH  Google Scholar 

  • Gribanov DV, Veselov SI (2016) On integer programming with bounded determinants. Optim Lett 10(6):1169–1177

    Article  MathSciNet  MATH  Google Scholar 

  • Gruber M, Lekkerkerker CG (1987) Geometry of numbers. North-Holland, Amsterdam

    MATH  Google Scholar 

  • Hanrot G, Pujol X, Stehle D (2011) Algorithms for the shortest and closest lattice vector problems. Lecture Notes in Computer Science, vol 6639, pp 159–190

  • Hu TC (1970) Integer programming and network flows. Addison-Wesley, Reading

    Google Scholar 

  • Kannan R (1983) Improved algorithms for integer programming and related lattice problems. In: Proceedings of 15th annual ACM symposium on theory of computing, pp 99–108

  • Kannan R (1987) Minkowski’s convex body theorem and integer programming. Math Oper Res 12(3):415–440

    Article  MathSciNet  MATH  Google Scholar 

  • Karmarkar N (1984) A new polynomial time algorithm for linear programming. Combinatorica 4(4):373–391

    Article  MathSciNet  MATH  Google Scholar 

  • Khachiyan LG (1980) Polynomial algorithms in linear programming. Comput Math Math Phys 20(1):53–72

    Article  MathSciNet  MATH  Google Scholar 

  • Lenstra HW (1983) Integer programming with a fixed number of variables. Math Oper Res 8(4):538–548

    Article  MathSciNet  MATH  Google Scholar 

  • Lenstra AK, Lenstra HW Jr, Lovasz L (1982) Factoring polynomials with rational coefficients. Math Ann 261:515–534

    Article  MathSciNet  MATH  Google Scholar 

  • Micciancio D, Voulgaris P (2010) A deterministic single exponential time algorithm for most lattice problems based on Voronoi cell computations. In: Proceedings of 42nd annual ACM symposium on theory of computing, pp 351–358

  • Nesterov YE, Nemirovsky AS (1994) Interior point polynomial methods in convex programming. Society for Industrial and Applied Mathematics, Philadelphia

    Book  Google Scholar 

  • Pardalos PM, Han CG, Ye Y (1991) Interior point algorithms for solving nonlinear optimization problems. COAL Newsl 19:45–54

    Google Scholar 

  • Schrijver A (1998) Theory of linear and integer programming. Wiley, London

    MATH  Google Scholar 

  • Sebö A (1999) An introduction to empty lattice simplicies. Lecture Notes in Computer Science, vol 1610, pp 400–414

  • Shevchenko VN (1996) Qualitative topics in integer linear programming (translations of mathematical monographs). AMS Book, Providence

    Book  Google Scholar 

  • Siegel CL (1989) Lectures on the geometry of numbers. Springer, Berlin

    Book  MATH  Google Scholar 

  • Storjohann A (1996) Near optimal algorithms for computing Smith normal forms of integer matrices. In: Proceedings of the 1996 international symposium on symbolic and algebraic computation, pp 267–274

  • Storjohann A, Labahn G (1996) Asymptotically fast computation of Hermite normal forms of integer matrices. In: Proceedings of the 1996 international symposium on symbolic and algebraic computation, pp 259–266

  • Tardos E (1986) A strongly polynomial algorithm to solve combinatorial linear programs. Oper Res 34(2):250–256

    Article  MathSciNet  MATH  Google Scholar 

  • Veselov SI, Chirkov AJ (2009) Integer program with bimodular matrix. Discrete Optim 6(2):220–222

    Article  MathSciNet  MATH  Google Scholar 

  • Zhendong W (2005) Computing the Smith forms of integer matrices and solving related problems. University of Delaware, Newark

    Google Scholar 

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Acknowledgements

Results of Sect. 3 were obtained under financial support of Russian Science Foundation Grant No. 14-41-00039. Results of Sect. 4 were obtained under financial support of Russian Science Foundation Grant No. 17-11-01336. Results of Sect. 5 were obtained under financial support of Russian Foundation for Basic Research, Grant No. 16-31-60008-mol-a-dk, and LATNA laboratory, NRU HSE.

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Correspondence to D. S. Malyshev.

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Gribanov, D.V., Malyshev, D.S., Pardalos, P.M. et al. FPT-algorithms for some problems related to integer programming. J Comb Optim 35, 1128–1146 (2018). https://doi.org/10.1007/s10878-018-0264-z

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