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Demand Forecasting Method Based on Stochastic Processes and Its Validation Using Real-World Data

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Applied and Numerical Partial Differential Equations

Part of the book series: Computational Methods in Applied Sciences ((COMPUTMETHODS,volume 15))

Abstract

Demand forecasting problems frequently arise in logistics and supply chain management. The Newsboy Problem is one such problem. In this paper, we present an improved solution method using application of the Black–Scholes model incorporating stochastic processes used in financial engineering for option pricing. Through numerical experiments using real-world data, the proposed model is demonstrated to be effective.

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References

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Author information

Authors and Affiliations

  1. Graduate School of Environmental Sciences, Okayama University, 3-1-1, Tsushima-naka, Okayama, 700-8530, Japan

    Yinggao Zheng & Hiroshi Suito

  2. Iwaki Credit Bank, 74-2, Shimokajiro-Yamakamisawa, Onahama, Iwaki, 970-0316, Japan

    Hideo Kawarada

Authors
  1. Yinggao Zheng
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  2. Hiroshi Suito
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  3. Hideo Kawarada
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Corresponding author

Correspondence to Yinggao Zheng .

Editor information

Editors and Affiliations

  1. Dept. Mathematics, University of Houston, Calhoun Road 4800, Houston, 77204-3008, U.S.A.

    W. Fitzgibbon

  2. Dept. Mathematics, University of Houston, Calhoun Road 4800, Houston, 77204-3008, U.S.A.

    Y.A. Kuznetsov

  3. Dept. Mathematical Information , University of Jyväsklyklä, Jyväskylä, 40351, Finland

    Pekka Neittaanmäki

  4. Numèrics en Enginyeria (CIMNE), Centre Internacional de Mètodes, C/ Gran Capitan s/n, Barcelona, 08034, Spain

    Jacques Périaux

  5. Dept. Mathematique, Université de Paris VI, place Jussieu 4 , Paris CX 05, 75252, France

    Olivier Pironneau

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Zheng, Y., Suito, H., Kawarada, H. (2010). Demand Forecasting Method Based on Stochastic Processes and Its Validation Using Real-World Data. In: Fitzgibbon, W., Kuznetsov, Y., Neittaanmäki, P., Périaux, J., Pironneau, O. (eds) Applied and Numerical Partial Differential Equations. Computational Methods in Applied Sciences, vol 15. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3239-3_11

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  • DOI: https://doi.org/10.1007/978-90-481-3239-3_11

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-3238-6

  • Online ISBN: 978-90-481-3239-3

  • eBook Packages: EngineeringEngineering (R0)

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