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Staff Scheduling with Particle Swarm Optimisation and Evolution Strategies

  • Conference paper
Evolutionary Computation in Combinatorial Optimization (EvoCOP 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5482))

Abstract

The current paper uses a scenario from logistics to show that modern heuristics, and in particular particle swarm optimization (PSO) can significantly add to the improvement of staff scheduling in practice. Rapid, sub-daily planning, which is the focus of our research offers considerable productivity reserves for companies but also creates complex challenges for the planning software.

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Author information

Authors and Affiliations

  1. Chair of Information Systems in Services, Technical University of Ilmenau, D-98684, Ilmenau, Germany

    Volker Nissen & Maik Günther

Authors
  1. Volker Nissen
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  2. Maik Günther
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Editor information

Editors and Affiliations

  1. Dept. Lenguajes y Ciencias de la Computación, ETSI Informática, Universidad de Málaga, Campus Teatinos, 29071, Málaga, Spain

    Carlos Cotta

  2. Department of Computing, University of Bradford, BD7 1DP, Bradford, UK

    Peter Cowling

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© 2009 Springer-Verlag Berlin Heidelberg

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Nissen, V., Günther, M. (2009). Staff Scheduling with Particle Swarm Optimisation and Evolution Strategies. In: Cotta, C., Cowling, P. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2009. Lecture Notes in Computer Science, vol 5482. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01009-5_20

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  • DOI: https://doi.org/10.1007/978-3-642-01009-5_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01008-8

  • Online ISBN: 978-3-642-01009-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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