Rostering with a Hybrid Genetic Algorithm

  • Matthias Gröbner
  • Peter Wilke


Human workforce is an expensive resource and therefore should be used as efficient as possible. This optimization task is quite difficult especially in situations where staff members are different in their skills, qualifications or the details of their employment contracts, i.e. these constraints make the optimization of rosters achallenging and difficult task. In this paper we show how Genetic Algorithms combined with problem specific knowledge can be successfully applied to solve such scheduling and planning problems.


Genetic Algorithm Repair Operator Penalty Cost Soft Constraint Late Shift 
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 Wien 2001

Authors and Affiliations

  • Matthias Gröbner
    • 1
  • Peter Wilke
    • 2
  1. 1.Universität Erlangen-NürnbergErlangenGermany
  2. 2.Centre for Intelligent Information Processing SystemsThe University of Western AustraliaNedlandsAustralia

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