When is it Feasible to Model Low Discrete Demand by a Normal Distribution?
(2011) In OR Spectrum: Quantitative Approaches in Management- Abstract
- Inventory control systems used in practice are quite often modeling the lead-time demand by a normal distribution. This may result in considerable errors when the real demand is low and discrete. For such demand, it is usually better to use a discrete demand distribution. However, this will increase the computational effort. A natural question is under what circumstances a normal approximation is feasible. This paper analyzes this question in a numerical study. Our study indicates that a normal approximation works reasonably well when the average lead-time demand is something like 10 or higher and the coefficient of variation is bounded by something like 2. The normal approximation works better for a high backorder cost or, equivalently, a... (More)
- Inventory control systems used in practice are quite often modeling the lead-time demand by a normal distribution. This may result in considerable errors when the real demand is low and discrete. For such demand, it is usually better to use a discrete demand distribution. However, this will increase the computational effort. A natural question is under what circumstances a normal approximation is feasible. This paper analyzes this question in a numerical study. Our study indicates that a normal approximation works reasonably well when the average lead-time demand is something like 10 or higher and the coefficient of variation is bounded by something like 2. The normal approximation works better for a high backorder cost or, equivalently, a high service level. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2026673
- author
- Axsäter, Sven LU
- organization
- publishing date
- 2011
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Inventory management, Stochastic, Low demand, Normal approximation
- in
- OR Spectrum: Quantitative Approaches in Management
- publisher
- Springer
- external identifiers
-
- wos:000313165800006
- scopus:84871948578
- ISSN
- 1436-6304
- DOI
- 10.1007/s00291-011-0278-8
- language
- English
- LU publication?
- yes
- id
- 384421bb-4165-4e51-a53c-c96745e19560 (old id 2026673)
- date added to LUP
- 2016-04-04 11:27:59
- date last changed
- 2023-01-05 23:58:11
@article{384421bb-4165-4e51-a53c-c96745e19560,
abstract = {{Inventory control systems used in practice are quite often modeling the lead-time demand by a normal distribution. This may result in considerable errors when the real demand is low and discrete. For such demand, it is usually better to use a discrete demand distribution. However, this will increase the computational effort. A natural question is under what circumstances a normal approximation is feasible. This paper analyzes this question in a numerical study. Our study indicates that a normal approximation works reasonably well when the average lead-time demand is something like 10 or higher and the coefficient of variation is bounded by something like 2. The normal approximation works better for a high backorder cost or, equivalently, a high service level.}},
author = {{Axsäter, Sven}},
issn = {{1436-6304}},
keywords = {{Inventory management; Stochastic; Low demand; Normal approximation}},
language = {{eng}},
publisher = {{Springer}},
series = {{OR Spectrum: Quantitative Approaches in Management}},
title = {{When is it Feasible to Model Low Discrete Demand by a Normal Distribution?}},
url = {{http://dx.doi.org/10.1007/s00291-011-0278-8}},
doi = {{10.1007/s00291-011-0278-8}},
year = {{2011}},
}