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- W122852371 abstract "We propose a novel approach to computing lower bounds for box-constrained mixed-integer polynomial minimization problems. Instead of considering convex relaxations, as in most common approaches, we determine a separable underestimator of the polynomial objective function, which can then be minimized easily over the feasible set even without relaxing integrality. The main feature of our approach is the fast computation of a good separable underestimator; this is achieved by computing tight underestimators monomialwise after an appropriate shifting of the entire polynomial. If the total degree of the polynomial objective function is bounded, it suffices to consider finitely many monomials, the optimal underestimators can then be computed offline and hardcoded. For the quartic case, we determine all optimal monomial underestimators analytically." @default.
- W122852371 created "2016-06-24" @default.
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- W122852371 date "2014-01-01" @default.
- W122852371 modified "2023-09-23" @default.
- W122852371 title "Box-Constrained Mixed-Integer Polynomial Optimization Using Separable Underestimators" @default.
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- W122852371 doi "https://doi.org/10.1007/978-3-319-07557-0_17" @default.
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