DipPy is a Python-based modeling language that provides a simple interface to DIP, a framework for implementing a variety of decomposition-based branch-and-bound algorithms for solving mixed integer linear programs). DipPy is an extension of PuLP (Python library for modeling linear and integer programs) that allows users to specify decompositions and customize the branching, cut generation, and column generation of DIP, from within a PuLP model. This interface greatly simplifies both the problem definition and the customization of the framework using that problem definition.
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References in zbMATH (referenced in 2 articles )
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- Hertz, Alain; Montagné, Romain; Gagnon, François: A comparison of integer programming models for the partial directed weighted improper coloring problem (2019)
- Bergner, Martin; Caprara, Alberto; Ceselli, Alberto; Furini, Fabio; Lübbecke, Marco E.; Malaguti, Enrico; Traversi, Emiliano: Automatic Dantzig-Wolfe reformulation of mixed integer programs (2015)