We present a new piecewise linear approximation of non-linear optimization problems. It can be seen as a variant of classical triangulations that leaves more degrees of freedom to define any point as a convex combination of the samples. We show theoretical properties of the approximating functions, and provide computational evidence of the impact of their use within MILP models approximating non-linear problems.
Riccardo Rovatti, Claudia D’Ambrosio, Andrea Lodi, Silvano Martello (2014). Optimistic MILP modeling of non-linear optimization problems. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 239, 32-45 [10.1016/j.ejor.2014.03.020].
Optimistic MILP modeling of non-linear optimization problems
ROVATTI, RICCARDO;LODI, ANDREA;MARTELLO, SILVANO
2014
Abstract
We present a new piecewise linear approximation of non-linear optimization problems. It can be seen as a variant of classical triangulations that leaves more degrees of freedom to define any point as a convex combination of the samples. We show theoretical properties of the approximating functions, and provide computational evidence of the impact of their use within MILP models approximating non-linear problems.File in questo prodotto:
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