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Robbins, H., Monro, S., “A Stochastic Approximation Method”, The Annals of Mathematical Statistics, 22(3). 400-407. Sep. 1951.

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Article

Solving the Newsvendor Problem using Stochastic Approximation: A Kiefer-Wolfowitz Algorithm Approach

1Department of Mathematical Sciences, Ball State University, Muncie IN, USA


American Journal of Applied Mathematics and Statistics. 2024, Vol. 12 No. 2, 24-27
DOI: 10.12691/ajams-12-2-1
Copyright © 2024 Science and Education Publishing

Cite this paper:
Quan Yuan, Zhixin Yang, Yayuan Xiao. Solving the Newsvendor Problem using Stochastic Approximation: A Kiefer-Wolfowitz Algorithm Approach. American Journal of Applied Mathematics and Statistics. 2024; 12(2):24-27. doi: 10.12691/ajams-12-2-1.

Correspondence to: Quan  Yuan, Department of Mathematical Sciences, Ball State University, Muncie IN, USA. Email: qyuan@bsu.edu

Abstract

This paper investigates the application of the Kiefer-Wolfowitz (KW) algorithm, a stochastic approximation technique, to solve the newsvendor problem under uncertain demand. The proposed approach enables the newsvendor to learn from observed profits and converge to the optimal order quantity, even when the demand distribution is unknown. Numerical experiments demonstrate the algorithm's effectiveness in handling stochastic demand and provide insights into its convergence properties. The paper highlights the potential of stochastic approximation methods in tackling inventory management challenges and discusses future research directions.

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