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Reconsidering Mixed Integer Programming and MIP-Based Hybrids for Scheduling

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Book cover Integration of AI and OR Techniques in Contraint Programming for Combinatorial Optimzation Problems (CPAIOR 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7298))

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.

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Author information

Authors and Affiliations

  1. Zuse Institute Berlin, Takustr. 7, 14195, Berlin, Germany

    Stefan Heinz

  2. Department of Mechanical & Industrial Engineering, University of Toronto, Toronto, Ontario, M5S 3G8, Canada

    J. Christopher Beck

Authors
  1. Stefan Heinz
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  2. J. Christopher Beck
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Editor information

Editors and Affiliations

  1. École des Mines de Nantes, 4, rue Alfred Kastler, 44307, Nantes Cedex 3, France

    Nicolas Beldiceanu

  2. École des Mines de Nantes, 4 rue Alfred Kastler, 44307, Nantes Cedex 3, France

    Narendra Jussien

  3. Institut de Mathématiques Appliquées, 44 rue Rabelais, 49008, Angers Cedex 01, France

    Éric Pinson

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© 2012 Springer-Verlag Berlin Heidelberg

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Heinz, S., Beck, J.C. (2012). Reconsidering Mixed Integer Programming and MIP-Based Hybrids for Scheduling. In: Beldiceanu, N., Jussien, N., Pinson, É. (eds) Integration of AI and OR Techniques in Contraint Programming for Combinatorial Optimzation Problems. CPAIOR 2012. Lecture Notes in Computer Science, vol 7298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29828-8_14

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  • DOI: https://doi.org/10.1007/978-3-642-29828-8_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29827-1

  • Online ISBN: 978-3-642-29828-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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