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When is it Feasible to Model Low Discrete Demand by a Normal Distribution?

Axsäter, Sven LU (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:
author
organization
publishing date
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
2011-07-15 08:26:50
date last changed
2016-11-15 14:36:05
@misc{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},
  keyword      = {Inventory management,Stochastic,Low demand,Normal approximation},
  language     = {eng},
  publisher    = {ARRAY(0xb7d8df8)},
  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},
  year         = {2011},
}