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Predicting Medicine Demand Fluctuations Through Markov Chain

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Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future (SOHOMA 2022)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1083))

Abstract

Nowadays, the healthcare sector is rapidly changing. Hospitals are facing limited budgets and high costs. The logistics activities of the hospitals in France (stock management, delivery, etc.) represent one of the highest cost components. The logistics costs can be reduced through an optimized inventory management system. The inventory optimization is strongly dependent on the accuracy of the demand prediction of medicines. Many factors influence this demand, such as seasonality, hospital size and location, etc. The objective of the paper is to propose a Markov chain model to estimate medicine demand fluctuations for hospital logistics in France. An analysis of the first experimental results is proposed to assess the effectiveness of the method. This preliminary result could contribute to the management of hospital inventories.

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Notes

  1. 1.

    The OECD’s 38 members are: Austria, Australia, Belgium, Canada, Chile, Colombia, Costa Rica, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Latvia, Lithuania, Luxembourg, Mexico, the Netherlands, New Zealand, Norway, Poland, Portugal, and Slovakia.

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Acknowledgement

This work has been partially supported by the MIAI Multidisciplinary AI Institute at the Univ. Grenoble Alpes: (MIAI@Grenoble Alpes - ANR-19-P3IA-0003).

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Authors and Affiliations

  1. Université Grenoble Alpes, CNRS, Grenoble INP G-SCOP, 38000, Grenoble, France

    Daniel Vélez, Siao-Leu Phouratsamay, Zakaria Yahouni & Gülgün Alpan

Authors
  1. Daniel Vélez
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  2. Siao-Leu Phouratsamay
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  3. Zakaria Yahouni
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  4. Gülgün Alpan
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Corresponding author

Correspondence to Zakaria Yahouni .

Editor information

Editors and Affiliations

  1. Faculty of Automatic Control and Computers, University Politehnica of Bucharest, Bucharest, Romania

    Theodor Borangiu

  2. LAMIH UMR CNRS 8201, Université Polytechnique Hauts de France UPHF, Valenciennes Cedex 9, France

    Damien Trentesaux

  3. Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Politecnico de Bragança, Bragança, Portugal

    Paulo Leitão

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Vélez, D., Phouratsamay, SL., Yahouni, Z., Alpan, G. (2023). Predicting Medicine Demand Fluctuations Through Markov Chain. In: Borangiu, T., Trentesaux, D., Leitão, P. (eds) Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. SOHOMA 2022. Studies in Computational Intelligence, vol 1083. Springer, Cham. https://doi.org/10.1007/978-3-031-24291-5_26

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