The Computational Complexity of Integer Programming with Alternations

被引:1
|
作者
Danny Nguyen [1 ]
Pak, Igor [2 ]
机构
[1] Univ Michigan, Dept Math, Ann Arbor, MI 48105 USA
[2] Univ Calif Los Angeles, Dept Math, Los Angeles, CA 90095 USA
基金
美国国家科学基金会;
关键词
integer programming; alternations; projection of integer points; RATIONAL GENERATING-FUNCTIONS;
D O I
10.1287/moor.2018.0988
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
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):538-5481 and Kannan [13,14] [Kannan R (1990) Test sets for integer programs, for all there exists 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):161-177.1 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 subset of 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.
引用
收藏
页码:191 / 204
页数:14
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