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Abstract

Despite the success of constraint programming (CP ) for scheduling, the much wider penetration of mixed integer programming (MIP ) technology into business applications means that many practical scheduling problems are being addressed with MIP, at least as an initial approach. Furthermore, there has been impressive and well-documented improvements in the power of generic MIP solvers over the past decade. We empirically demonstrate that on an existing set of resource allocation and scheduling problems standard MIP and CP models are now competitive with the state-of-the-art manual decomposition approach. Motivated by this result, we formulate two tightly coupled hybrid models based on constraint integer programming (CIP ) and demonstrate that these models, which embody advances in CP and MIP, are able to out-perform the CP, MIP, and decomposition models. We conclude that both MIP and CIP are technologies that should be considered along with CP for solving scheduling problems.

Keywords

Schedule Problem Mixed Integer Programming Constraint Programming Master Problem Linear Relaxation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Stefan Heinz
    • 1
  • J. Christopher Beck
    • 2
  1. 1.Zuse Institute BerlinBerlinGermany
  2. 2.Department of Mechanical & Industrial EngineeringUniversity of TorontoTorontoCanada

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