A geometric way to build strong mixed-integer programming formulations
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Abstract (arXiv)
We give an explicit geometric way to build mixed-integer programming (MIP) formulations for unions of polyhedra. The construction is simply described in terms of spanning hyperplanes in an r-dimensional linear space. The resulting MIP formulation is ideal, and uses exactly r integer variables and 2 x (# of spanning hyperplanes) general inequality constraints. We use this result to derive novel logarithmic-sized ideal MIP formulations for discontinuous piecewise linear functions and structures appearing in robotics and power systems problems.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Nov 2018.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 0; 2025: 0; 2026: 2.
3 papers.
- 2022Mixed integer linear optimization formulations for learning optimal binary classification treescited by 4
- 2026Computation of Least Trimmed Squares: A Branch-and-Bound framework with Hyperplane Arrangement Enhancementscited by 1
- 2026Coordinate Optimality Reformulation for Mixed-Integer Convex Programs with Indicatorscited by 0
- 2026Coordinate Optimality Reformulation for Mixed-Integer Convex Programs with Indicators2 Aug 2026
- 2026Computation of Least Trimmed Squares: A Branch-and-Bound framework with Hyperplane Arrangement Enhancements13 Apr 2026
- 2022Mixed integer linear optimization formulations for learning optimal binary classification trees10 Jun 2022