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.
