Digital Capacity Optimizer v4.0 - Research Edition: Risk & Resilience (Stable))

🏆 Milestone: Commit #200 Release

This release marks the transition of the LSP Digital Capacity Twin from a stochastic prototype to a stable Research Decision Support System (DSS). It operationalizes the "Pixels to Premiums" framework with a focus on quantifying global trade risks and network resilience.

🌪️ Strategic Additions

• Resilience Simulator: Added a formal "Stress Test" mode to evaluate network recovery during exogenous shocks (e.g., port strikes, labor disruptions).
• Risk Quantification Engine: Implemented 10,000-iteration Monte Carlo simulations to calculate Value at Risk (VaR 95%) and Loss Probability (%P_loss).
• Global Sourcing Module: Integrated CBAM (Carbon Border Adjustment Mechanism) and FTA (Free Trade Agreement) simulators to quantify "China Plus One" strategies.

🛠️ Stability & Maintenance

• Health Diagnostics: New health_check.py to validate API gateways and database connectivity.
• Version Automation: Added version_sync.py to ensure metadata consistency across the package.
• Hardened Math: Refactored inventory_math.py to handle zero-demand edge cases and prevent domain errors in stochastic calculations.

📊 Methodological Foundation

This version strictly follows the Wallenburg (2011) framework for LSP resilience and incorporates the Root Sum of Squares (RSS) method for dual-uncertainty safety stock modeling.

Digital Capacity Optimizer v3.0 - LSP Digital Capacity Twin: Resilience & Cooperation Edition (Stable)

🚛 Research Artifact: LSP Digital Capacity Twin (v3.0.0)

This major release pivots the artifact from a general inventory model to a specialized Decision Support System (DSS) for Logistics Service Providers (LSPs). It operationalizes key theoretical frameworks regarding horizontal cooperation and supply chain resilience.

🔬 New Research Modules

• Horizontal Cooperation Engine: Mathematically models the cost and operational impact of outsourcing overflow capacity to competitors (The "Frenemy" model).
• Resilience Index: Introduces a composite score (0-100) quantifying a service lane's ability to absorb volatility shocks.
• Reverse Logistics Volatility: Added logic to simulate the capacity load of e-commerce returns.
• Cost Convexity Analysis: Visual proof of the "U-Shaped" cost curve to validate optimal service level targets.

🛠 Technical Enhancements

• PhD-Grade Synthetic Data: Added seed_data.py to generate realistic scenarios (Industrial Overflow, Pharma Shocks, Seasonal Returns).
• Verification Suite: Added tests.py to unit-test the resilience and cooperation algorithms.
• Architecture: Refactored inventory_math.py into a robust logic layer separating calculation from presentation.

📊 Methodology

• Optimization: Stochastic Newsvendor Model (Critical Fractile).
• Risk: Root Sum of Squared (RSS) Volatility Integration.
• Stack: Python 3.11, Streamlit, PostgreSQL, Scipy.

Digital Capacity Optimizer v2.0 - Enterprise Edition SQL + Docker) (Stable)

🚀 Major Update: Enterprise Architecture

This release transitions the application from a local script to a fully containerized, database-backed web application.

New Features

• 🔌 PostgreSQL Integration: Replaced CSV storage with a production-grade SQL database.
• 📝 Write Capability: Users can now log new inventory transactions directly via the UI.
• 📦 Docker Support: Added Dockerfile for containerized deployment.
• 🥪 Sandbox Mode: Toggle between Live Database and CSV Uploads for scenario testing.
• 💅 UI Polish: Improved form inputs and error handling.

Tech Stack Upgrades

• Added SQLAlchemy for ORM.
• Added psycopg2 for Postgres connection.
• Added Plotly for interactive charts.

Digital Capacity Optimizer v1.0 (Stable)

🚀 Features

• Predictive Engine: Holt-Winters forecasting for demand trends.
• Web Dashboard: Interactive Streamlit interface.
• Risk Modelling: Newsvendor Logic with Service Level optimisation.
• Quality: Automated CI/CD pipeline with unit tests.