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Publication Detailed Description
Cost-effective and operationally sustainable supply chain inventory planning: A mathematical programming approach
Marketing and smart technologies: Proceedings of ICMarkTech 2024
Year (definitive publication)
2025
Language
English
Country
Singapore
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Abstract
The concerns about economically and operationally sustainable supply chains are increasingly at the forefront. It is urgent to create innovative models and less costly systems. This can be achieved through using more efficient supply chains and the rational use of resources. Inventory management has been widely studied by several authors. Nevertheless, there is still a small number of studies exploring its application at the supply chain level, despite being widely recognized that the collaboration between partners in the supply chain is critical to achieve more efficient inventory management decisions. In fact, such a collaboration fosters the global optimization of supply chains. The inventory supply chain planning problem is addressed through the use of the continuous review (r, Q) policy, aiming at optimizing inventories throughout a supply chain while defining the amount of products transported among facilities over time. For that purpose, a mixed integer linear programming model is constructed, and a supply chain with multiple periods, multiple warehouses, and multiple retailers is modeled as a reference. This model adds to existing literature on supply chain inventory management by extending existing models to a supply chain with multiple periods and warehouses. The model, hereafter called CRP2InvSC model, allows to determine inventory levels, order quantities Q and reorder points r for each time period and each facility on a supply chain. Products flows between supply chain entities are also modeled. To demonstrate the applicability of the proposed model, a supply network case study is utilized.
Acknowledgements
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Keywords
Supply chain management,Inventory planning,Mixed integer linear programming,Continuous review policy
Fields of Science and Technology Classification
- Mathematics - Natural Sciences
- Computer and Information Sciences - Natural Sciences
- Other Social Sciences - Social Sciences
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