Order-up-to-level policy update procedure for a supply chain subject to market demand uncertainty
•We propose a new dynamic order policy for a supply chain with uncertainty in demand.•Inventory consumption occurs at random time intervals and demand a random quantity of items.•The new order policy avoids propagation of uncertainty through SC levels.•This policy mitigates the bullwhip effect, mini...
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| Published in | Computers & industrial engineering Vol. 113; pp. 347 - 355 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
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01.11.2017
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| Abstract | •We propose a new dynamic order policy for a supply chain with uncertainty in demand.•Inventory consumption occurs at random time intervals and demand a random quantity of items.•The new order policy avoids propagation of uncertainty through SC levels.•This policy mitigates the bullwhip effect, minimizes stockout, and increases the customer service level.
The planning of a supply chain (SC) subject to market demand uncertainty is challenging in regards to defining update mechanisms that deal with demand variations. This study addresses this challenge and proposes a new reorder point update procedure for order-up-to-level (OUTL) policies in continuous review systems. The new procedure modifies the classical OUTL policy by introducing absorption inventory, a concept that changes reorder points and lot sizes according to demand variations. Results obtained through a discrete event simulation based on real-world data provided by a Brazilian company show that the proposed order policy provides better performance, particularly in terms of bullwhip effect reduction and improved service level. |
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| AbstractList | •We propose a new dynamic order policy for a supply chain with uncertainty in demand.•Inventory consumption occurs at random time intervals and demand a random quantity of items.•The new order policy avoids propagation of uncertainty through SC levels.•This policy mitigates the bullwhip effect, minimizes stockout, and increases the customer service level.
The planning of a supply chain (SC) subject to market demand uncertainty is challenging in regards to defining update mechanisms that deal with demand variations. This study addresses this challenge and proposes a new reorder point update procedure for order-up-to-level (OUTL) policies in continuous review systems. The new procedure modifies the classical OUTL policy by introducing absorption inventory, a concept that changes reorder points and lot sizes according to demand variations. Results obtained through a discrete event simulation based on real-world data provided by a Brazilian company show that the proposed order policy provides better performance, particularly in terms of bullwhip effect reduction and improved service level. |
| Author | Cannella, Salvatore Pacheco, Eduardo de Oliveira Barbosa-Povoa, Ana Paula Lüders, Ricardo |
| Author_xml | – sequence: 1 givenname: Eduardo de Oliveira surname: Pacheco fullname: Pacheco, Eduardo de Oliveira email: doutoradopacheco@gmail.com organization: DAINF/CPGEI, Federal University of Technology – Paraná, Av. Sete de Setembro 3165, 80230-901 Curitiba-PR, Brazil – sequence: 2 givenname: Salvatore surname: Cannella fullname: Cannella, Salvatore email: cannella@unict.it, cannella@us.es organization: DICAR – University of Catania, Via A. Doria 5, 95131 Catania, Italy – sequence: 3 givenname: Ricardo surname: Lüders fullname: Lüders, Ricardo email: luders@utfpr.edu.br organization: DAINF/CPGEI, Federal University of Technology – Paraná, Av. Sete de Setembro 3165, 80230-901 Curitiba-PR, Brazil – sequence: 4 givenname: Ana Paula surname: Barbosa-Povoa fullname: Barbosa-Povoa, Ana Paula email: apovoa@tecnico.ulisboa.pt organization: Centro de Estudos de Gestão, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa, Portugal |
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| SubjectTerms | Bullwhip effect Discrete event simulation Inventory control Order-up-to-level policy Supply chain |
| Title | Order-up-to-level policy update procedure for a supply chain subject to market demand uncertainty |
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