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Particle Swarm Optimization and an Agent-Based Algorithm for a Problem of Staff Scheduling

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Book cover Applications of Evolutionary Computation (EvoApplications 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6025))

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Abstract

Eight problems of a practical staff scheduling application from logistics are used to compare the effectiveness and efficiency of two fundamentally different solution approaches. One can be called centralized and is based on search in the solution space with an adapted metaheuristic, namely particle swarm optimization (PSO). The second approach is decentralized. Artificial agents negotiate to construct a staff schedule. Both approaches significantly outperform todays manual planning. PSO delivers the best overall results in terms of solution quality and is the method of choice, when CPU-time is not limited. The agent approach is vastly quicker in finding solutions of almost the same quality as PSO. The results suggest that agents could be an interesting method for real-time scheduling or re-scheduling tasks.

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Authors and Affiliations

  1. Information Systems in Services, Ilmenau University of Technology, D-98684, Ilmenau

    Maik Günther & Volker Nissen

Authors
  1. Maik Günther
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  2. Volker Nissen
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Statistics, University of Strathclyde, 16 Richmond Street, G1 1XQ, Glasgow, UK

    Cecilia Di Chio

  2. School of Business, University College Dublin, Belfield, Dublin 4, UK

    Anthony Brabazon

  3. ’Dalla Molle’ Institute for Artificial Intelligence (IDSIA), Galleria 2, 6928, Manno-Lugano, Switzerland

    Gianni A. Di Caro

  4. Wilhelm Schickard-Institut für Informatik, Universität Tübingen, Sand 1, 72076, Tübingen, Germany

    Marc Ebner

  5. National University of Computer and Emerging Sciences (NUCES), A.K. Brohi Road, H-11/4, Islamabad, Pakistan

    Muddassar Farooq

  6. Fakultät für WiSo, HelmutSchmidt-Universität, Holstenhofweg 85, 22043, Hamburg, Germany

    Andreas Fink

  7. Department of Information Systems, Johannes Gutenberg-Universität, 55099, Mainz, Germany

    Jörn Grahl

  8. Mathematics and Computer Science Depatment, University of Richmond, 23173, Richmond, VA, USA

    Gary Greenfield

  9. Department of Informatics Engineering, Polo II - Pinhal de Marrocos, University of Coimbra, 3030 - 290, Coimbra, Portugal

    Penousal Machado

  10. School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, UK

    Michael O’Neill

  11. Istituto di Calcolo e Reti ad Alte Prestazioni (ICAR), Consiglio Nazionale delle Ricerche (CNR), Via P. Castellino 111, 80131, Naples, Italy

    Ernesto Tarantino

  12. School of Computing, Edinburgh Napier University, 10 Clinton Road, EH10 5DT, Edinburgh, UK

    Neil Urquhart

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Günther, M., Nissen, V. (2010). Particle Swarm Optimization and an Agent-Based Algorithm for a Problem of Staff Scheduling. In: Di Chio, C., et al. Applications of Evolutionary Computation. EvoApplications 2010. Lecture Notes in Computer Science, vol 6025. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12242-2_46

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  • DOI: https://doi.org/10.1007/978-3-642-12242-2_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12241-5

  • Online ISBN: 978-3-642-12242-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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