Polynomial Upper Bounds on the Number of Differing Columns of ?-Modular Integer Programs
成果类型:
Article
署名作者:
Lee, Jon; Paat, Joseph; Stallknecht, Ingo; Xu, Luze
署名单位:
University of Michigan System; University of Michigan; University of British Columbia
刊物名称:
MATHEMATICS OF OPERATIONS RESEARCH
ISSN/ISSBN:
0364-765X
DOI:
10.1287/moor.2022.1339
发表日期:
2023
页码:
2267-2286
关键词:
摘要:
We study integer-valued matrices with bounded determinants. Such matrices appear in the theory of integer programs (IPs) with bounded determinants. For example, an IP can be solved in strongly polynomial time if the constraint matrix is bimodular: that is, the determinants are bounded in absolute value by two. Determinants are also used to bound the euro1 distance between IP solutions and solutions of its linear relaxation. One of the first to quantify the complexity of IPs with bounded determinants was Heller, who identified the maximum number of differing columns in a totally unimodular matrix. Each extension of Heller's bound to general determinants has been superpolynomial in the determinants or the number of equations. We provide the first column bound that is polynomial in both values. For integer programs with box constraints, our result gives the first euro1 distance bound that is polynomial in the determinants and the number of equations. Our result can also be used to derive a bound on the height of Graver basis elements that is polynomial in the determinants and the number of equations. Furthermore, we show a tight bound on the number of differing columns in a bimodular matrix; this is the first tight bound since Heller. Our analysis reveals combinatorial properties of bimodular IPs that may be of independent interest.
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