Title
Solving the newsvendor problem under parametric uncertainty using simulation
Date Issued
16 February 2016
Access level
metadata only access
Resource Type
conference output
Author(s)
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
In this paper, we discuss the formulation and solution to the newsvendor problem under a Bayesian framework that allows the incorporation of uncertainty on the parameters of the demand model (introduced by the estimation process of these parameters). We present an application of this model with an analytical solution and we conduct experiments to compare the results under the proposed method and a classical approach. Furthermore, we illustrate the estimation of the optimal order size using stochastic simulation, when the complexity of the model does not allow the finding of a closed form expression for the solution.
Start page
2078
End page
2087
Volume
2016-February
Language
English
OCDE Knowledge area
Ingeniería eléctrica, Ingeniería electrónica
Scopus EID
2-s2.0-84962877294
ISBN
9781467397438
ISSN of the container
08917736
Conference
Proceedings - Winter Simulation Conference
Sources of information: Directorio de Producción Científica Scopus