Mathematical Model for Centralized Supply Chains with Decisions Involving Shared Resources
Context: Cooperation in supply chain management is an important issue considering the global performance of the different echelons of a specific supply chain. In this sense, applying logistic strategies such as VMI (Vendor Managed Inventory) allows a system to manage distribution processes from a ce...
Main Authors: | , , |
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Format: | Article |
Language: | Spanish |
Published: |
Universidad Distrital Francisco José de Caldas
2020-10-01
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Series: | Ingeniería |
Subjects: | |
Online Access: | https://revistas.udistrital.edu.co/index.php/reving/article/view/16921 |
Summary: | Context: Cooperation in supply chain management is an important issue considering the global performance of the different echelons of a specific supply chain. In this sense, applying logistic strategies such as VMI (Vendor Managed Inventory) allows a system to manage distribution processes from a central point or depot. Additionally, the components of the chain work more closely with it, which allows increasing global performance, instead of individually developing each sector.
Method: A stochastic mathematical model is proposed which considers a network of customers, where products are delivered from a central depot. These customers can share part of their product with the central depot for redistribution, aiming to minimize shortage for other customers. A mathematical model is proposed which includes the elements involved in distribution processes. It is then reformulated to consider shortage and the linearization of some of its elements.
Results: Results show that implementing or adapting logistic strategies, such as managing from a central point and sharing resources along the supply chain, allows companies to reduce the complexity of some decisions and improve performance.
Conclusions: Implementing logistic strategies such as centralized management and sharing resources along a supply network allows companies to reduce the complexity of some decisions and, in turn, improve their performance. |
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ISSN: | 0121-750X 2344-8393 |