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High performance integer optimization for crew scheduling

  • Peter Sanders
  • Tuomo Takkula
  • Dag Wedelin
Track C1: (Industrial) End-user Applications of HPCN
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1593)

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 and a new sequential active set strategy which requires less work and is better adapted to the memory hierachy properties of modern RISC processors. The active set strategy can even be parallelized on networks of workstations.

Keywords

Lagrangian Relaxation Crew Schedule Global Iteration Innermost Loop Good Load Balance 
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 1999

Authors and Affiliations

  • Peter Sanders
    • 1
  • Tuomo Takkula
    • 2
  • Dag Wedelin
    • 2
  1. 1.Max-Planck-Institute for Computer ScienceSaarbrückenGermany
  2. 2.Chalmers University of Technology, Computing ScienceGöteborgSweden

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