Mixed-integer linear representability, disjunctions, and Chvatal functions --- modeling implications
Amitabh Basu, Kipp Martin, Christopher Thomas Ryan, Guanyi Wang

TL;DR
This paper provides an algebraic characterization of MILP-representable sets using affine Chvatal inequalities, simplifying the modeling process and resolving a long-standing open question about elimination schemes without disjunctions.
Contribution
It introduces an algebraic characterization of MILP-representable sets via affine Chvatal inequalities, eliminating the need for disjunctions in modeling and solving open problems in the field.
Findings
MILP-R sets are exactly those describable by affine Chvatal inequalities with integer variables.
Projection of sets defined by affine Chvatal inequalities remains MILP-R.
A sequential elimination scheme yields the AC set characterization, answering Ryan's open question.
Abstract
Jeroslow and Lowe gave an exact geometric characterization of subsets of that are projections of mixed-integer linear sets, also known as MILP-representable or MILP-R sets. We give an alternate algebraic characterization by showing that a set is MILP-R {\em if and only if} the set can be described as the intersection of finitely many {\em affine Chvatal inequalities} in continuous variables (termed AC sets). These inequalities are a modification of a concept introduced by Blair and Jeroslow. Unlike the case for linear inequalities, allowing for integer variables in Chvatal inequalities and projection does not enhance modeling power. We show that the MILP-R sets are still precisely those sets that are modeled as affine Chvatal inequalites with integer variables. Furthermore, the projection of a set defined by affine Chvatal inequalites with integer variables is still an…
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Taxonomy
TopicsComplexity and Algorithms in Graphs · Advanced Optimization Algorithms Research · Constraint Satisfaction and Optimization
