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.
https://projects.coin-or.org/Dip
It is quite beneficial to talk with Matt about DIP. I learnt a lot during our discussions. Thanks Matt.
Regarding the design of DIP. We need to treat master-only variables differently, which I did not realize before.
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