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This is a Quantitative Study study (also classified as: Experimental Study).

Modeling and optimization of cooperative multi-warehouse inventory systems under uncertainty: A scenario-based probabilistic programming approach

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This study demonstrates an optimization approach for multi-warehouse inventory systems, suggesting improved decision-making under uncertainty.

The model delivers optimal inventory decisions, enhancing profitability in supply chain management under uncertainty.
Computational experiments validated the model's effectiveness in generating decisions, with optimal outcomes in fluctuating demand scenarios.
A robust mathematical programming model was developed and implemented using Python and Gurobi, addressing the complexities of multi-warehouse systems.
Insights gained offer practical strategies for supply chain stakeholders to improve operational resilience during unpredictable conditions.

Sutrisno et al. (2025) studied this question.

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This study demonstrates an optimization approach for multi-warehouse inventory systems, suggesting improved decision-making under uncertainty.