State reduction in a dependent demand inventory model given by a time series

The dependent demand inventory model given by the time series with a stochastic trend and seasonality was considered. A two-state variable dynamic programming problem was reduced to the one-state variable problem under linear cost structure. The demand distribution was shown to be normal with the no...

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Published inEuropean journal of operational research Vol. 41; no. 2; pp. 174 - 180
Main Author Reyman, Grzegorz
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 25.07.1989
Elsevier
Elsevier Sequoia S.A
SeriesEuropean Journal of Operational Research
Subjects
Online AccessGet full text
ISSN0377-2217
1872-6860
DOI10.1016/0377-2217(89)90381-0

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Abstract The dependent demand inventory model given by the time series with a stochastic trend and seasonality was considered. A two-state variable dynamic programming problem was reduced to the one-state variable problem under linear cost structure. The demand distribution was shown to be normal with the nonstationary mean and the constant variance. The optimal ordering levels are characterized by single critical numbers.
AbstractList The dependent demand inventory model given by the time series with a stochastic trend and seasonality was considered. A two-state variable dynamic programming problem was reduced to the one-state variable problem under linear cost structure. The demand distribution was shown to be normal with the nonstationary mean and the constant variance. The optimal ordering levels are characterized by single critical numbers.
In practice, researchers are very often confronted with dynamic inventory problems of dependent demand. However, not much research has been conducted on this subject. Generally, stochastic models assume that demand distributions in inventory in different periods are independent. Recently, more attention has been given to dependent demand inventory models. Generally, the exponential forecasting model is considered. However, a more general model for a dependent demand is examined. The time series is given by a stochastic trend component and a seasonal component. A 2-state variable dynamic programming problem is reduced to the one-state variable problem under a linear cost structure. The demand distribution is shown to be normal with the nonstationary mean and the constant variance. The optimal ordering levels are attained by single critical numbers.
Author Reyman, Grzegorz
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Cites_doi 10.1287/mnsc.31.9.1150
10.1287/opre.34.1.83
10.1287/mnsc.6.3.231
10.1002/nav.3800070428
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Issue 2
Keywords time series
demand
Inventory
Demand
Stockpile control
Reduction method
Seasonal demand
Time series
Bayes forecasting
Models
Dynamic programming
Two variables function
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Snippet The dependent demand inventory model given by the time series with a stochastic trend and seasonality was considered. A two-state variable dynamic programming...
In practice, researchers are very often confronted with dynamic inventory problems of dependent demand. However, not much research has been conducted on this...
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SubjectTerms Applied sciences
Demand
Dynamic programming
Exact sciences and technology
Inventory
Inventory control
Inventory control, production control. Distribution
Lagermanagement
Mathematical models
Operational research and scientific management
Operational research. Management science
Operations research
Reduction
State
Theorie
Time series
Zeitreihenanalyse
Title State reduction in a dependent demand inventory model given by a time series
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