supply-chain-analytics

GUAC aggregates software security metadata into a high fidelity graph database.

blint is a Binary Linter that checks the security properties and capabilities of your executables. It can also generate a Software Bill-of-Materials (SBOM) for supported binaries.

A project on using mathematical programming to solve multi-modal transportation cost minimization in goods delivery and supply chain management.

Improve Warehouse Productivity using Order Batching

Supply Chain Forecast Accuracy 2026: MAPE, Bias & FVA Dashboard

Advanced MS SQL Server & Power BI Data Warehousing & Fleet Logistics Engine 2026

SupplyGraph | A Benchmark Dataset for Supply Chain Planning using Graph Neural Networks

Python implementation to solve Vehicle Routing problem & Master Production Scheduling in Supply Chain Analytics & Design.

Author: Feras Al-Basha; Research Director: Yossiri Adulyasak; Research Director: Laurent Charlin; MSc in Global Supply Chain Management - Mémoire/Thesis; HEC Montréal.

Project based on business intelligence and visualisation for supply chain domain using Power BI and supply chain KPIs

A Python library to design & optimize Supply Chains

A low capacity and high capacity plant across 5 countries are considered and a linear programming model is built to determine the total lowest costs for satisfying consumer demand across all countries, based on various constraints. Data visualization is done and interactive widgets are used to compare different scenarios.

Deterministic and Stochastic Dynamic Programs for optimization of Supply Chain

The official Python library for the Log-hub API

In this study, we aimed to detect fraudulent activities in the supply chain through the use of neural networks. The study focused on building two machine learning models using the MLPClassifier algorithm from the scikit-learn library and a custom neural network using the Keras library in Python.

Shiny App for Warehouse location Determination

Understanding the supply chain process data and implementing different algorithms, building a machine learning model that can predict whether a given order gets cancelled or goes to back order.

An end-to-end data analytics project featuring supply chain data insights to derive actionable insights that can help optimize inventory management, improve delivery performance, and enhance overall efficiency in the supply chain process

In this article, we explored a comprehensive supply chain analytics project, encompassing data extraction, ETL using Python, loading data into Snowflake, and creating an interactive dashboard with Power BI. By harnessing the power of ETL, Snowflake, and Power BI, businesses can unlock valuable insights from their supply chain data.

Forecast-driven inventory optimization project for retail demand planning, combining SARIMAX, ML model comparison, feasibility auditing, Monte Carlo simulation, and inventory policy optimization.