MIP

Linear, Integer, and Constraint Programming

Description

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

• the SCIP Optimization Suite

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.

Contact

Timo Berthold

Members

• Timo Berthold

• Gerald Gamrath

• Ambros Gleixner

• Martin Grötschel

• Stefan Heinz

• Thorsten Koch

• Matthias Miltenberger

• Yuji Shinano

• Kati Wolter

Partners

• Siemens AG: Corporate Technology
• TU Darmstadt: Discrete Optimization
• RWTH Aachen: Chair of Operations Research
• University of Erlangen-Nürnberg: Chair of EDOM

Duration

since 01/1994 until further notice