Detailed Information

Cited 6 time in webofscience Cited 9 time in scopus
Metadata Downloads

A note on a robust inventory model with stock-dependent demand

Authors
Lim, Sungmook
Issue Date
4-May-2019
Publisher
TAYLOR & FRANCIS LTD
Keywords
Stock-dependent demand; inventory model; robust optimisation; periodic-review model; convex optimisation
Citation
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, v.70, no.5, pp 851 - 866
Pages
16
Indexed
SCI
SCIE
SSCI
SCOPUS
Journal Title
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
Volume
70
Number
5
Start Page
851
End Page
866
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/8121
DOI
10.1080/01605682.2018.1468861
ISSN
0160-5682
1476-9360
Abstract
We investigate an inventory model with stock-dependent demand where larger pile of stock displayed leads the customer to purchase more. The dependency of demand on the inventory level is modelled as a monomial function whose shape and scale parameters are stochastic. We present a linear regression-based method for constructing ellipsoidal representations of the parameter uncertainty, which are subsequently incorporated into the inventory model under the robust optimisation framework. We show that the resulting robust optimisation model can be transformed into an equivalent convex programme, and also prove that a robust optimal inventory replenishment policy is of the base-stock type. Through a numerical illustration of the proposed approach and a performance analysis based upon Monte Carlo simulation, we demonstrate that robust optimal order decisions exhibit a unique advantage over deterministic ones.
Files in This Item
There are no files associated with this item.
Appears in
Collections
Dongguk Business School > Department of Business Administration > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Lim, Sung Mook photo

Lim, Sung Mook
Dongguk Business School (Department of Business Administration)
Read more

Altmetrics

Total Views & Downloads

BROWSE