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

Yinggao Zheng, Hiroshi Suito, Hideo Kawarada

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationComputational Methods in Applied Sciences
PublisherSpringer Netherland
Pages147-160
Number of pages14
Volume15
DOIs
Publication statusPublished - 2010

Publication series

NameComputational Methods in Applied Sciences
Volume15
ISSN (Print)18713033

    Fingerprint

ASJC Scopus subject areas

  • Computational Mathematics
  • Modelling and Simulation
  • Fluid Flow and Transfer Processes
  • Computer Science Applications
  • Civil and Structural Engineering
  • Electrical and Electronic Engineering
  • Biomedical Engineering

Cite this

Zheng, Y., Suito, H., & Kawarada, H. (2010). Demand Forecasting Method Based on Stochastic Processes and Its Validation Using Real-World Data. In Computational Methods in Applied Sciences (Vol. 15, pp. 147-160). (Computational Methods in Applied Sciences; Vol. 15). Springer Netherland. https://doi.org/10.1007/978-90-481-3239-3_11