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 leadtime 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 leadtime 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 leadtime 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 leadtime 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:
http://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
 14366304
 DOI
 10.1007/s0029101102788
 language
 English
 LU publication?
 yes
 id
 384421bb41654e51a53cc96745e19560 (old id 2026673)
 date added to LUP
 20110715 08:26:50
 date last changed
 20170212 04:26:24
@article{384421bb41654e51a53cc96745e19560, abstract = {Inventory control systems used in practice are quite often modeling the leadtime 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 leadtime 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 = {14366304}, keyword = {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/s0029101102788}, year = {2011}, }