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Optimizing Complex Multi-location Inventory Models Using Particle Swarm Optimization

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Computational Optimization, Methods and Algorithms

Part of the book series: Studies in Computational Intelligence ((SCI,volume 356))

Abstract

The efficient control of logistics systems is a complicated task. Analytical models allow to estimate the effect of certain policies. However, they necessitate the introduction of simplifying assumptions, and therefore, their scope is limited. To surmount these restrictions, we use Simulation Optimization by coupling a simulator that evaluates the performance of the system with an optimizer. This idea is illustrated for a very general class of multi-location inventory models with lateral transshipments. We discuss the characteristics of such models and introduce Particle Swarm Optimization for their optimization. Experimental studies show the applicability of this approach.

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Author information

Authors and Affiliations

  1. Manufacturing Coordination and Technology, Bosch Rexroth AG, 97816, Lohr am Main, Germany

    Christian A. Hochmuth

  2. Institute of Computational Science, University of Lugano, Via Giuseppe Buffi 13, 6906, Lugano, Switzerland

    Jörg Lässig

  3. Institute of Physics, Chemnitz University of Technology, 09107, Chemnitz, Germany

    Stefanie Thiem

Authors
  1. Christian A. Hochmuth
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  2. Jörg Lässig
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  3. Stefanie Thiem
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Editor information

Editors and Affiliations

  1. School of Science and Engineering Engineering Optimization & Modeling Center, Reykjavik University, Menntavegur 1, 101, Reykjavik, Iceland

    Slawomir Koziel

  2. Mathematics and Scientific Computing, National Physical Laboratory, TW11 0LW, Teddington, UK

    Xin-She Yang

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© 2011 Springer-Verlag Berlin Heidelberg

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Hochmuth, C.A., Lässig, J., Thiem, S. (2011). Optimizing Complex Multi-location Inventory Models Using Particle Swarm Optimization. In: Koziel, S., Yang, XS. (eds) Computational Optimization, Methods and Algorithms. Studies in Computational Intelligence, vol 356. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20859-1_6

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  • DOI: https://doi.org/10.1007/978-3-642-20859-1_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20858-4

  • Online ISBN: 978-3-642-20859-1

  • eBook Packages: EngineeringEngineering (R0)

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