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The Computational Complexity of Integer Programming with Alternations

Author

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  • Danny Nguyen

    (Department of Mathematics, University of Michigan, Ann Arbor, Michigan 48105;)

  • Igor Pak

    (Department of Mathematics, University of California, Los Angeles, Los Angeles, California 90095)

Abstract

We prove that integer programming with three alternating quantifiers is NP-complete, even for a fixed number of variables. This complements earlier results by Lenstra [ 16 ] [Lenstra H ( 1983 ) Integer programming with a fixed number of variables. Math. Oper. Res. 8(4):538–548.] and Kannan [ 13, 14 ] [Kannan R ( 1990 ) Test sets for integer programs, ∀ ∃ sentences. Polyhedral Combinatorics (American Mathematical Society, Providence, RI), 39–47. Kannan R ( 1992 ) Lattice translates of a polytope and the Frobenius problem. Combinatorica 12(2):161–177.], which together say that integer programming with at most two alternating quantifiers can be done in polynomial time for a fixed number of variables. As a byproduct of the proof, we show that for two polytopes P , Q ⊂ R 3 , counting the projections of integer points in Q\P is #P-complete. This contrasts the 2003 result by Barvinok and Woods [ 5 ] [Barvinok A, Woods K ( 2003 ) Short rational generating functions for lattice point problems. J. Amer. Math. Soc. 16(4):957–979.], which allows counting in polynomial time the projections of integer points in P and Q separately.

Suggested Citation

  • Danny Nguyen & Igor Pak, 2020. "The Computational Complexity of Integer Programming with Alternations," Mathematics of Operations Research, INFORMS, vol. 45(1), pages 191-204, February.
    • Handle: RePEc:inm:ormoor:v:45:y:2020:i:1:p:191-204
    DOI: 10.1287/moor.2018.0988
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    References listed on IDEAS

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    1. H. W. Lenstra, 1983. "Integer Programming with a Fixed Number of Variables," Mathematics of Operations Research, INFORMS, vol. 8(4), pages 538-548, November.
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