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Constraint Integer Programming: a New Approach to integrate CP and MIP (2008)
| Citations: | 34 - 7 self |
BibTeX
@MISC{Achterberg08constraintinteger,
author = {Tobias Achterberg and Timo Berthold and Thorsten Koch and Kati Wolter},
title = {Constraint Integer Programming: a New Approach to integrate CP and MIP},
year = {2008}
}
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Abstract
This article introduces constraint integer programming (CIP), which is a novel way to combine constraint programming (CP) and mixed integer programming (MIP) methodologies. CIP is a generalization of MIP that supports the notion of general constraints as in CP. This approach is supported by the CIP framework SCIP, which also integrates techniques from SAT solving. SCIP is available in source code and free for noncommercial use. We demonstrate the usefulness of CIP on two tasks. First, we apply the constraint integer programming approach to pure mixed integer programs. Computational experiments show that SCIP is almost competitive to current state-of-the-art commercial MIP solvers. Second, we employ the CIP framework to solve chip design verification problems, which involve some highly non-linear constraint types that are very hard to handle by pure MIP solvers. The CIP approach is very effective here: it can apply the full sophisticated MIP machinery to the linear part of the problem, while dealing with the non-linear constraints by employing constraint programming techniques.
Keyphrases
constraint integer programming source code computational experiment non-linear constraint type cip framework cip approach linear part pure mip solver full sophisticated mip machinery constraint programming current state-of-the-art commercial mip solver mixed integer programming chip design verification problem constraint integer general constraint novel way noncommercial use non-linear constraint mixed integer program cip framework scip
