Motivated by the perspective use in decomposition-based generic Mixed Integer Programming (MIP) solvers, we consider the problem of scoring Dantzig-Wolfe decomposition patterns. In particular, assuming to receive in input a MIP instance, we tackle the issue of estimating the tightness of the dual bound yielded by a particular decomposition of that MIP instance, and the computing time required to obtain such a dual bound, looking only at static features of the corresponding data matrices. We propose decomposition ranking methods. We also sketch and evaluate an architecture for an automatic data-driven detector of good decompositions.
Computational evaluation of ranking models in an automatic decomposition framework / S. Basso, A. Ceselli. - In: ELECTRONIC NOTES IN DISCRETE MATHEMATICS. - ISSN 1571-0653. - 69:(2018), pp. 245-252. ((Intervento presentato al convegno EURO-ALIO tenutosi a Bologna nel 2018 [10.1016/j.endm.2018.07.032].
Computational evaluation of ranking models in an automatic decomposition framework
S. Basso;A. Ceselli
2018
Abstract
Motivated by the perspective use in decomposition-based generic Mixed Integer Programming (MIP) solvers, we consider the problem of scoring Dantzig-Wolfe decomposition patterns. In particular, assuming to receive in input a MIP instance, we tackle the issue of estimating the tightness of the dual bound yielded by a particular decomposition of that MIP instance, and the computing time required to obtain such a dual bound, looking only at static features of the corresponding data matrices. We propose decomposition ranking methods. We also sketch and evaluate an architecture for an automatic data-driven detector of good decompositions.File | Dimensione | Formato | |
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