Granularity for Mixed-Integer Polynomial Optimization Problems Article Swipe
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Carl Eggen
,
Oliver Stein
,
Stefan Volkwein
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1007/s10957-025-02631-6
· OA: W4408197251
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1007/s10957-025-02631-6
· OA: W4408197251
Finding good feasible points is crucial in mixed-integer programming. For this purpose we combine a sufficient condition for consistency, called granularity, with the moment-/sum-of-squares-hierarchy from polynomial optimization. If the mixed-integer problem is granular, we obtain feasible points by solving continuous polynomial problems and rounding their optimal points. The moment-/sum-of-squares-hierarchy is hereby used to solve those continuous polynomial problems, which generalizes known methods from the literature. Numerical examples from the MINLPLib illustrate our approach.
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