2d-cutting-stock

Collection of Supply chain skills, implementations, papers and agents

Instalação
CLI
npx skills add https://github.com/kishorkukreja/awesome-supply-chain --skill 2d-cutting-stock

Instale esta skill com a CLI e comece a usar o fluxo de trabalho SKILL.md em seu espaço de trabalho.

Última atualização em 4/23/2026

Awesome Supply Chain

A comprehensive collection of research papers, implementations, libraries, and resources for supply chain management, organized by industry verticals.

132 AI Agent Skills Available!** This repository now includes a complete Claude Code plugin with supply chain skills for AI coding assistants. See Skills Documentation →

Table of Contents

Overview

This repository consolidates the latest research, papers, implementations, and development libraries related to supply chain use cases across different industry verticals. It serves as a curated resource for researchers, practitioners, and developers working on supply chain optimization, management, and analytics.

AI Skills Plugin

This repository includes 132 comprehensive AI agent skills that work as a plugin for Claude Code and other AI coding assistants. These skills give your AI assistant expert knowledge in:

  • Supply Chain Planning - Demand forecasting, S&OP, capacity planning
  • Operations Research - VRP, TSP, facility location, knapsack, cutting stock
  • Inventory Management - EOQ, safety stock, multi-echelon optimization
  • Warehouse Operations - Slotting, routing, wave planning, automation
  • Transportation - Route optimization, fleet management, last-mile delivery
  • Manufacturing - Production scheduling, lean, quality management
  • Domain Expertise - Retail, CPG, energy, healthcare, travel, manufacturing

Quick Start

# Clone the repository
git clone https://github.com/kishorkukreja/awesome-supply-chain.git

# Install skills to Claude Code
cd awesome-supply-chain
cp -r skills/* ~/.claude/skills/

Full Skills Documentation: skills/README.md

Plugin Configuration: .claude/README.md

Industry Verticals

Consumer Packaged Goods (CPG)

Supply chain research and implementations specific to consumer packaged goods industry, including network optimization, demand planning, and distribution strategies.

Retail

Retail supply chain management research covering omnichannel fulfillment, inventory optimization, last-mile delivery, and consumer-centric approaches.

Manufacturing

Manufacturing supply chain topics including smart manufacturing, Industry 4.0, production planning, and digital twins.

Industrial

Industrial supply chain research covering heavy equipment, B2B procurement, industrial IoT, and smart factories.

Energy

Energy supply chain optimization including renewable energy, oil & gas logistics, energy storage systems, and sustainable energy networks.

Transportation & Logistics

Transportation and logistics optimization covering route planning, fleet management, warehouse operations, and last-mile delivery.

Travel & Hospitality

Tourism and hospitality supply chain management including hotel operations, tour operators, and service chain optimization.

Cross-Industry

Research and solutions applicable across multiple industries, including general supply chain principles and emerging technologies.

General Research

Core Topics

  • Machine Learning & AI: Deep learning, reinforcement learning, and predictive analytics for supply chain
  • Optimization: Mathematical optimization, linear programming, metaheuristics
  • Digital Technologies: Blockchain, IoT, Digital Twins, Cloud Computing
  • Sustainability: Green supply chain, circular economy, carbon footprint reduction
  • Risk Management: Supply chain resilience, disruption management, scenario planning
  • Demand Forecasting: Time series analysis, forecasting models, demand sensing
  • Inventory Management: Stock optimization, safety stock, multi-echelon inventory
  • Network Design: Facility location, distribution network optimization

Libraries & Tools

Python Libraries

Popular Python libraries for supply chain analysis and optimization:

  • supplychainpy: Supply chain analysis, modeling and simulation
  • PuLP: Linear programming
  • OR-Tools: Google's optimization tools
  • NetworkX: Network analysis and optimization
  • Prophet: Time series forecasting
  • TensorFlow/PyTorch: Deep learning frameworks

Data & Analytics Tools

  • Tableau: Supply chain visualization
  • Power BI: Business intelligence and analytics
  • Apache Spark: Big data processing
  • Apache Kafka: Real-time data streaming

Implementations

GitHub Repositories

Curated list of open-source implementations:

  • Supply chain optimization algorithms
  • Demand forecasting models
  • Inventory management systems
  • Route optimization solutions
  • Warehouse management systems
  • Supply chain simulation frameworks

Key Research Themes (2024-2025)

Emerging Technologies

  • Generative AI: ChatGPT and LLMs for supply chain planning
  • Digital Twins: Virtual replicas for simulation and optimization
  • Autonomous Systems: Self-driving vehicles, drones, robots
  • 5G & Edge Computing: Real-time decision making at the edge

Sustainability Focus

  • Carbon footprint reduction and tracking
  • Circular economy and closed-loop supply chains
  • Sustainable sourcing and ethical procurement
  • Green logistics and eco-friendly transportation

Resilience & Risk

  • Supply chain resilience frameworks
  • Multi-sourcing and supplier diversification
  • Scenario planning and risk mitigation
  • Real-time visibility and control towers

Contributing

We welcome contributions! Please follow these guidelines:

  1. Adding Papers: Include title, authors, publication venue, year, and DOI/link
  2. Adding Implementations: Provide repository link, description, and key features
  3. Adding Libraries: Include installation instructions, use cases, and examples
  4. Adding/Improving Skills: Contribute to the AI skills in the skills/ directory
  5. Quality Standards: Ensure resources are from reputable sources and are recent (preferably 2020+)

Contributing Skills

The skills/ directory contains 132 AI agent skills for supply chain problems. To contribute:

  1. Follow the existing skill structure (YAML frontmatter + markdown content)
  2. Include working Python code examples
  3. Add relevant algorithms and frameworks
  4. Reference industry best practices
  5. See skills/README.md for detailed guidelines

Research Sources

  • Academic journals (Scopus, Web of Science, Google Scholar)
  • Conference proceedings (ACM, IEEE, INFORMS)
  • Industry reports (Gartner, McKinsey, Forrester)
  • Open-source repositories (GitHub, GitLab)
  • Preprint servers (arXiv, SSRN)

License

This repository is maintained for educational and research purposes. Please respect the licenses of individual papers, libraries, and implementations.

Maintainers

This repository is actively maintained and updated with the latest research and developments in supply chain management.


Last Updated: October 2025