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Inventory optimization toolkit featuring deterministic lot-sizing models, stochastic safety-stock and newsvendor formulations, a Tkinter/Matplotlib GUI, full pytest coverage, and an RL environment to benchmark PPO policies against optimal dynamic programming.
🏢 End-to-end Inventory Data Analysis project covering Demand Forecasting, ABC Analysis, EOQ, Inventory Turnover, Lead Time, and Carrying Cost Optimization.
Data-driven retail inventory optimization project using Power BI dashboards, demand forecasting, EOQ, and replenishment strategies to minimize costs and ensure optimal stock levels.