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. DIP is used in combination with CHiPPS, which provides
the underlying tree search methodology.

• Eugeny A. Rostovtsev
• Vitaly Kuznetsov

• CoinDip
• CoinDip-data
• CoinDip-debuginfo
• CoinDip-examples
• libCoinDip
• libCoinDip-debuginfo
• libCoinDip-devel