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DIP (Decomposition for Integer Programming) is an open-source extensible software framework for implementing decomposition-based bounding algorithms for use in solving large-scale discrete optimization problems. The framework provides a simple API for experimenting with various decomposition-based algorithms, such as Dantzig-Wolfe decomposition, Lagrangian relaxation, and various cutting plane methods. Given a compact formulation and a relaxation, the framework takes care of all algorithmic details associated with implementing any of a wide range of decomposition-based algorithms, such as branch and cut, branch and price, branch and cut and price, subgradient-based Lagrangian relaxation, branch and relax and cut, and decompose and cut. The user can specify customizations, such as methods for generating valid inequalities and branching, in terms of the variables of the compact formulation, without having to worry about the details of any required reformulations.
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