Skip to content
#

reorder-point

Here are 25 public repositories matching this topic...

End-to-end café inventory project: clean transaction data, build daily item-level demand series, backtest strong baseline forecasters, generate next-30-day demand forecasts, convert forecasts into safety stock + reorder points, and validate policies with Monte Carlo stockout-risk simulations, wrapped in a Streamlit dashboard.

  • Updated Feb 9, 2026
  • Python

Demand forecasting and reorder point analysis on 540k retail transactions — with a warehouse manager's decision memo, honest baseline comparisons, and every number in the writeup independently verifiable from raw data.

  • Updated Aug 19, 2026
  • Python
Inventory-Forecasting-Optimizing-Engine

XGBoost-powered demand forecasting & reorder alert system for e-commerce — flags stockouts before they happen and surfaces cash trapped in overstock. Nightly auto-retraining via GitHub Actions.

  • Updated Sep 3, 2026
  • Python

AI-driven inventory optimization & 30-day demand forecasting app (Python, Pandas, Streamlit). Live sliders for supplier lead time and target service level instantly recompute safety stock and reorder points per store/item. Deployed on Streamlit Cloud.

  • Updated Oct 22, 2026
  • Jupyter Notebook

Measures what fill rate a textbook 95% cycle service policy actually delivers, and what closing the gap costs. Period by period inventory simulation with an analytic referee, undershoot measured rather than corrected away.

  • Updated Oct 20, 2026
  • Python

Add this topic to your repo

To associate your repository with the reorder-point topic, visit your repo's landing page and select "manage topics."

Learn more