The integrated inventory model simultaneously optimizes both order quantity (Q) and reorder level (R), treating them as interdependent variables rather than calculating them sequentially. This unified approach recognizes that the optimal Q depends on the chosen R through total cost functions, and vice versa, yielding different results than classical methods that derive Q from EOQ formula then calculate R independently. The model assumes probabilistic demand during lead time and seeks the combination of Q and R that minimizes total annual inventory cost (holding, ordering, and shortage costs). Table of Contents: • Integrated model framework: simultaneous optimization of two decision variables • Order quantity (Q) and reorder level (R) interdependencies • Separation fallacy: limitations of sequential optimization (EOQ then R) • Probabilistic demand during lead time as core assumption • Total cost function structure: holding costs + ordering costs + shortage costs • Mathematical formulation and optimization methodology • Comparison with decoupled approaches (traditional Q then R calculation) • Service level constraints and their integration into the cost function • Impact on decision-making: how integrated results differ from sequential methods • Application to practical supply chain planning scenarios
The integrated inventory model simultaneously optimizes both order quantity (Q) and reorder level (R), treating them as interdependent variables rather than calculating them sequentially. This unifie…