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Two-Echelon System Stochastic Optimization with R and CUDA

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Parallel Processing and Applied Mathematics (PPAM 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10777))

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Abstract

Parallelizing of the supply chain simulator is considered in this paper. The simulator is a key element of the algorithm optimizing inventory levels and order sizes in a two-echelon logistic system. The mode of operation of the logistic system and the optimization problem are defined first. Then, the inventory optimization algorithm is introduced. Parallelization for CUDA platform is presented. Benchmarking of the parallelized code demonstrates high efficiency of the software hybrid.

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References

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Author information

Authors and Affiliations

  1. Institute of Computing Science, Poznań University of Technology, Poznań, Poland

    Witold Andrzejewski & Maciej Drozdowski

  2. School of Mathematical Sciences, Tongji University, Shanghai, China

    Gang Mu & Yong Chao Sun

  3. F. Hoffmann-La Roche AG, Basel, Switzerland

    Gang Mu

Authors
  1. Witold Andrzejewski
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  2. Maciej Drozdowski
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  3. Gang Mu
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  4. Yong Chao Sun
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Corresponding author

Correspondence to Maciej Drozdowski .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technology, Czestochowa, Poland

    Roman Wyrzykowski

  2. University of Tennessee, Knoxville, Tennessee, USA

    Jack Dongarra

  3. University of Southern California, Marina Del Rey, California, USA

    Ewa Deelman

  4. Czestochowa University of Technology, Czestochowa, Poland

    Konrad Karczewski

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Andrzejewski, W., Drozdowski, M., Mu, G., Sun, Y.C. (2018). Two-Echelon System Stochastic Optimization with R and CUDA. In: Wyrzykowski, R., Dongarra, J., Deelman, E., Karczewski, K. (eds) Parallel Processing and Applied Mathematics. PPAM 2017. Lecture Notes in Computer Science(), vol 10777. Springer, Cham. https://doi.org/10.1007/978-3-319-78024-5_23

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  • DOI: https://doi.org/10.1007/978-3-319-78024-5_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78023-8

  • Online ISBN: 978-3-319-78024-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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