economic-order-quantity

Calculate economic order quantity (EOQ) by inputting annual demand, unit cost, ordering cost, and holding cost rate into the Python model to get the optimal order size that minimizes total inventory expenses.

EOQ determines the optimal order quantity for purchased items, while EPQ calculates the economic production quantity for internally produced items, both balancing setup and holding costs to minimize inventory expenses.

Yes, you can calculate reorder points to trigger replenishment before stockouts and incorporate backorder costs to optimize order quantities when planned stockouts are permissible in your supply chain.

Analyze all-units discount structures using the EOQ model to evaluate cost trade-offs across discount tiers, identifying the most cost-effective order quantity that minimizes total purchasing and holding costs.

Yes, the Python implementation of deterministic demand models for EOQ and EPQ calculations requires numpy and pandas dependencies to process inventory parameters and compute optimal ordering quantities.

Yes, matplotlib is a required dependency for the inventory optimization models, allowing you to visualize cost curves and order quantity relationships for EOQ and EPQ supply chain analysis.