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Parallel Integer Optimization for Crew Scheduling

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Abstract

Performance aspects of a Lagrangian relaxation based heuristic for solving large 0-1 integer linear programs are discussed. In particular, we look at its application to airline and railway crew scheduling problems. We present a scalable parallelization of the original algorithm used in production at Carmen Systems AB, Göteborg, Sweden, based on distributing the variables. A lazy variant of this approach which decouples communication and computation is even useful on networks of workstations. Furthermore, we develop a new sequential active set strategy which requires less work and is better adapted to the memory hierarchy properties of modern RISC processors. This algorithm is also suited for parallelization on a moderate number of networked workstations.

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Authors and Affiliations

  1. University of Patras, Patras, Greece

    Panayiotis Alefragis

  2. Max-Planck-Institute for Computer Science, Saarbrücken, Germany

    Peter Sanders

  3. Chalmers University of Technology, SE-412 96, Göteborg, Sweden

    Tuomo Takkula & Dag Wedelin

Authors
  1. Panayiotis Alefragis
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  2. Peter Sanders
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  3. Tuomo Takkula
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  4. Dag Wedelin
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Alefragis, P., Sanders, P., Takkula, T. et al. Parallel Integer Optimization for Crew Scheduling. Annals of Operations Research 99, 141–166 (2000). https://doi.org/10.1023/A:1019293017474

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