Integer Hulls, Z-Polyhedra and Presburger Arithmetic in Action

When solving systems of polynomial equations and inequalities, the task of computing their solutions with integer coordinates is a much harder problem than that of computing their real solutions or that of computing all their solutions. In fact, in the presence of non-linear constraints, this task may simply become an undecidable problem [12, 15]. However, studying the integer solutions of linear systems of equations and inequalities is of practical importance in various areas of scientific computing. Two such areas are combinatorial optimization (in particular, integer linear programming) and compiler optimization (in particular, the analysis, transformation, and scheduling of nested loops in computer programs), where a variety of algorithms solve questions related to the points with integer coordinates in a given polyhedron. Another area is at the crossroads of computer algebra and polyhedral geometry, with topics such as toric ideals and Hilbert bases, see [16], as well as the manipulation of Laurent series, see [1].

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Publication Details

Journal
ACM communications in computer algebra
Published
2025-09-01
DOI
https://doi.org/10.1145/3787957.3787958
Citations
1
Primary Topic
Polynomial and algebraic computation
Type
article
Field-Weighted Citation Impact
1.50
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article

Integer Hulls, Z-Polyhedra and Presburger Arithmetic in Action

Christopher F. S. Maligec, Rui-Juan Jing, Y. Skylar Lei, Marc Moreno Maza et al.
1 citations
ACM communications in computer algebra
Polynomial and algebraic computation
1.50
article

Integer Hulls, Z-Polyhedra and Presburger Arithmetic in Action

Christopher F. S. Maligec, Rui-Juan Jing, Y. Skylar Lei, Marc Moreno Maza, Chirantan Mukherjee
article en
1 citations

Abstract

When solving systems of polynomial equations and inequalities, the task of computing their solutions with integer coordinates is a much harder problem than that of computing their real solutions or that of computing all their solutions. In fact, in the presence of non-linear constraints, this task may simply become an undecidable problem [12, 15]. However, studying the integer solutions of linear systems of equations and inequalities is of practical importance in various areas of scientific computing. Two such areas are combinatorial optimization (in particular, integer linear programming) and compiler optimization (in particular, the analysis, transformation, and scheduling of nested loops in computer programs), where a variety of algorithms solve questions related to the points with integer coordinates in a given polyhedron. Another area is at the crossroads of computer algebra and polyhedral geometry, with topics such as toric ideals and Hilbert bases, see [16], as well as the manipulation of Laurent series, see [1].

ACM communications in computer algebraVol. 59(3)
Jiangsu University (CN), Western University (CA)
Openalex Percentile: Top 11%
Polynomial and algebraic computation
1.50
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