Linear, Integer, and Constraint Programming
Many real world problems can be modeled as mixed integer programs (MIPs) or mixed integer nonlinear programs (MINLPs). This project aims at developing tools for modeling and solving general MIPs and MINLPs, which can be applied by users as stand alone products or as a library within other software applications. We develop, maintain, and provide
which contains software for generating and solving linear programs (LPs), MIPs, MINLPs, and constraint integer programs.
The SCIP Optimization Suite includes:
- the modeling language ZIMPL
- the simplex LP-solver SoPlex
- the branch-cut-and-price framework, MIP- and MINLP-solver SCIP, integrating constraint programming and MIP
- the generic branch-and-price solver GCG
- the parallel framework UG for solving mixed integer linear and nonlinear programs
Furthermore, the LP-basis verifier perPlex is hosted at ZIB.
Further information is available in the detailed project description.
- Siemens AG: Corporate Technology
- TU Darmstadt: Discrete Optimization
- RWTH Aachen: Chair of Operations Research
- University of Erlangen-Nürnberg: Chair of EDOM
since 01/1994 until further notice