What is constraint integer programming?
by Timo Berthold
Abstract: Mixed-integer programming (MIP) and constraint programming (CP) proved to be a powerful tools to model and solve large-scale optimization problems. Constraint integer programming (CIP) is a novel generalization of MIP that supports the notion of arbitrary constraints as in CP. We introduce the basic notion and algorithmic ideas of CIP. Further, we present the software SCIP which is a solver and framework for constraint integer programming that also features SAT solving techniques. SCIP is available in source code and free for non-commercial use.
We illustrate the algorithmic design and the main sequence of the solving steps. Furthermore, we describe the various algorithmic components that enrich the basic CIP framework and discuss their role in the solving process. In this talk, we will mainly focus on techniques for solving mixed-integer programs.
Computational experiments indicating the potential of the approach are provided.
Bio: Timo is one of the chief developers of SCIP (an integer programming solving framework developed at Zuse Institute Berlin). He is an expert on primal heuristics and branching rules for mixed-integer linear and nonlinear programs.
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