Optimizing Inventory Management in the Supply Chain Using Mathematical Models: A Comprehensive Research Framework

This research synthesizes advanced mathematical modeling approaches designed for supply chain inventory optimization. By analyze integrated capacity-inventory coordination, vendor-managed inventory systems, nonlinear discount structures, and adaptive control mechanisms, this research show how mathematical optimization notably enhance supply chain flexibility and efficiency. This research analysis reveal that: linearization techniques for nonlinear capacity constraints decrease total costs by 12–18% while guaranteeing worldwide optima; VMI coordination algorithms reduce bullwhip effects by 20–30% under constrained capacities; and model-free adaptive control reduces inventory deviation by 25% in extremely volatile environments. The paper establish a combined framework for selecting and deploying optimization models based on supply chain characteristics, providing actionable insights for practitioners navigate demand uncertainty, multi-echelon complexity, and sustainability constraints.