Dual bounded generation: Polynomial, second-order cone and positive semidefinite matrix inequalities

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Abstract

In the monotone integer dualization problem, we are given two sets of vectors in an integer box such that no vector in the first set is dominated by a vector in the second. The question is to check if the two sets of vectors cover the entire integer box by upward and downward domination, respectively. It is known that the problem is (quasi-)polynomially equivalent to that of enumerating all maximal feasible solutions of a given monotone system of linear/separable/supermodular inequalities over integer vectors. The equivalence is established via showing that the dual family of minimal infeasible vectors has size bounded by a (quasi-)polynomial in the sizes of the family to be generated and the input description. Continuing in this line of work, in this paper, we consider systems of polynomial, second-order cone, and semidefinite inequalities. We give sufficient conditions under which such bounds can be established and highlight some applications.

Original languageBritish English
Pages (from-to)173-188
Number of pages16
JournalDiscrete Applied Mathematics
Volume364
DOIs
StatePublished - 31 Mar 2025

Keywords

  • Chance-constrained knapsack
  • Enumeration algorithm
  • Integer dualization
  • Polynomial inequality
  • Positive semidefinite inequality
  • Second-order cone inequality

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