Optimizing Safety Stock Placement in Large Real-World Automotive Supply Networks Using the Guaranteed-Service Model
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Date
2024-01-03
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1669
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Abstract
This paper presents an optimization model for the placement of safety stocks in multi-echelon supply networks using the Guaranteed-service Model. Our model handles complex network topologies and multiple products while examining the impact of service level and service time on total costs, formulated with mixed-integer linear programming. We utilize a unique network dataset acquired through data mining of financial databases to generate scenarios that reflect the complexities of real-world supply networks of five major automotive corporations. Experimental results validate the effectiveness of a dynamic-programming based solver in obtaining optimal solutions within large general network topologies. Furthermore, a sensitivity analysis reveals a negative correlation between safety stock costs and the maximum allowed service and a positive correlation between safety stock costs and the service level.
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Simulation Modeling and Digital Twins for Decision Making in the Age of Industry 4.0, guaranteed-service model, inventory management, multi-echelon inventory optimization, network science, supply chain management
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10 pages
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Proceedings of the 57th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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