Service Constrained (s, S) Inventory Systems with Priority Demand Classes and Lost Sales

This paper presents a model of an ( s , S ) inventory system in which there are two priority classes of customers. The model treats excess demands as lost sales and can accommodate an arbitrary deterministic lead time. After considering the associated Markov-chain model, an approximate, renewal-base...

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Published inManagement science Vol. 34; no. 4; pp. 482 - 499
Main Authors Cohen, Morris A, Kleindorfer, Paul R, Lee, Hau L
Format Journal Article
LanguageEnglish
Published Linthicum, MD INFORMS 01.04.1988
Institute of Management Sciences
Institute for Operations Research and the Management Sciences
SeriesManagement Science
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Abstract This paper presents a model of an ( s , S ) inventory system in which there are two priority classes of customers. The model treats excess demands as lost sales and can accommodate an arbitrary deterministic lead time. After considering the associated Markov-chain model, an approximate, renewal-based model is derived. This approximation is used to develop a greedy heuristic which minimizes expected costs subject to a fill-rate service constraint. The paper concludes with the results of an extensive numerical test of both the accuracy of the approximation and the performance of the heuristic with respect to the true optimal solution. Results indicate good performance which deteriorates as the fill rate requirement and lead time increase.
AbstractList This paper presents a model of an ( s , S ) inventory system in which there are two priority classes of customers. The model treats excess demands as lost sales and can accommodate an arbitrary deterministic lead time. After considering the associated Markov-chain model, an approximate, renewal-based model is derived. This approximation is used to develop a greedy heuristic which minimizes expected costs subject to a fill-rate service constraint. The paper concludes with the results of an extensive numerical test of both the accuracy of the approximation and the performance of the heuristic with respect to the true optimal solution. Results indicate good performance which deteriorates as the fill rate requirement and lead time increase.
This paper presents a model of an ( s , S ) inventory system in which there are two priority classes of customers. The model treats excess demands as lost sales and can accommodate an arbitrary deterministic lead time. After considering the associated Markov-chain model, an approximate, renewal-based model is derived. This approximation is used to develop a greedy heuristic which minimizes expected costs subject to a fill-rate service constraint. The paper concludes with the results of an extensive numerical test of both the accuracy of the approximation and the performance of the heuristic with respect to the true optimal solution. Results indicate good performance which deteriorates as the fill rate requirement and lead time increase.
Author Kleindorfer, Paul R
Lee, Hau L
Cohen, Morris A
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Snippet This paper presents a model of an ( s , S ) inventory system in which there are two priority classes of customers. The model treats excess demands as lost...
This paper presents a model of an ( s , S ) inventory system in which there are two priority classes of customers. The model treats excess demands as lost...
This paper presents a model of an (s, S) inventory system in which there are two priority classes of customers. The model treats excess demands as lost sales...
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SubjectTerms Applied sciences
Approximation
approximations
Business orders
Cost allocation
Cost functions
Exact sciences and technology
Greedy algorithms
Inventories
inventory
Inventory control, production control. Distribution
inventory/production
Lagermanagement
Markov chains
Minimization of cost
Operational research and scientific management
Operational research. Management science
Optimal solutions
ordering
production
Shipments
stochastic models
Theorie
Wahrscheinlichkeitsrechnung
Title Service Constrained (s, S) Inventory Systems with Priority Demand Classes and Lost Sales
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