MINLPLib--A Collection of Test Models for Mixed-Integer Nonlinear Programming

Authors:
Michael R. Bussieck;Arne Stolbjerg Drud;Alexander Meeraus
Affiliations:
-;-;-
Venue:
INFORMS Journal on Computing
Year:
2003

Citing 0
Cited 16

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IPCO'11 Proceedings of the 15th international conference on Integer programming and combinatoral optimization
Experiments with a feasibility pump approach for nonconvex MINLPs

SEA'10 Proceedings of the 9th international conference on Experimental Algorithms
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SO-MI: A surrogate model algorithm for computationally expensive nonlinear mixed-integer black-box global optimization problems

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On branching rules for convex mixed-integer nonlinear optimization

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Abstract

The paper describes a new computerized collection of test models for mixed-integer nonlinear programming. Because there is no standard format for nonlinear models, the model collection is augmented with a translation server that can transform the models from their basic GAMS format into other formats, including AMPL, BARON, LGO, LINGO, and MINOPT. The translation server can also be used to transform industrial models that contain confidential information. Such transformations allow many of these models to be distributed to the research community as highly relevant algorithmic test models.