What Is SCIP?

A similar technique is used for solving both Integer Programs and Constraint Programs: the problem is successively divided into smaller subproblems (branching) that are solved recursively.

On the other hand, Integer Programming and Constraint Programming have different strengths: Integer Programming uses LP relaxations and cutting planes to provide strong dual bounds, while Constraint Programming can handle arbitrary (non-linear) constraints and uses propagation to tighten domains of variables.

SCIP is a framework for Constraint Integer Programming oriented towards the needs of Mathematical Programming experts who want to have total control of the solution process and access detailed information down to the guts of the solver. SCIP can also be used as a pure MIP solver or as a framework for branch-cut-and-price.

SCIP is implemented as C callable library and provides C++ wrapper classes for user plugins. It can also be used as a standalone program to solve mixed integer programs given in MPS Format, in ILOG LP Format or as ZIMPL model.

An outline of SCIP and its algorithmic approach can be found in
Constraint Integer Programming: a New Approach to Integrate CP and MIP
Tobias Achterberg, Timo Berthold, Thorsten Koch, Kati Wolter
Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2008, LNCS 5015, 2008

A detailed description of SCIP can be found in
Constraint Integer Programming
Tobias Achterberg
Ph.D. thesis, TU Berlin, July 2007.

A printed version of the Ph.D. thesis is available at Verlag Dr. Hut, ISBN: 978-3-89963-892-9