Economics at your fingertips  

A methodology for stochastic inventory modelling with ARMA triangular distribution for new products

Fernando Rojas

Cogent Business & Management, 2017, vol. 4, issue 1, 1270706

Abstract: This paper proposes a stochastic inventory policy of continuous review with random demand described with temporal dependence through an autoregressive moving average (ARMA) model with explicative variables, of usefulness in new products without a history of demand data, assuming a triangular distribution. Optimization of the cost function related to the inventory model is obtained considering the expected value and variance marginal stationary of the demand per unit time and stochastic programming. The proposed policy is exemplified with real-world demand data from a Chilean hospital, where the demand of products (drugs) are correlated with other products and autocorrelated. The proposed methodology shows a useful tool for administrators who must decide optimal batch sizes and their reorder points when there is a low availability of demand data and is known to have a temporal structure.

Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from

Access Statistics for this article

Cogent Business & Management is currently edited by Len Tiu Wright and Tahir Nisar

More articles in Cogent Business & Management from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

Page updated 2019-02-27
Handle: RePEc:taf:oabmxx:v:4:y:2017:i:1:p:1270706