Supply Chain and Logistics Optimization: Graph Resilience

A supply chain is not a "Chain." It is a Global Graph. If a specific factory in Taiwan goes offline, it doesn't just stop "Production A." It stops the 15 sub-components that are used in 100 different products sold in 50 countries. Tabular data (Excel/ERP) is terrible at showing this "Ripple Effect." Graph RAG is built for exactly this.

In this lesson, we will look at how to build a Global Dependency Graph. We will learn how to perform Impact Analysis (answering the question: "If this ship is delayed, which 5-star customers will be affected?"). We will see how an AI agent can reason through thousands of logistics links to suggest the Shortest Alternative Path during a disaster.

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1. The Logistics Graph Schema

• (:Factory) {location, capacity}
• (:Part) {SKU, lead_time}
• (:Product) {BOM_list}
• (:Shipment) {ETA, status}
• (:Customer) {priority, location}

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2. Impact Analysis (The Downstream Crawl)

When a disruption happens (e.g., a port closure):

1. Tag the Node: Mark the Port node as status: Blocked.
2. Breadth-First Search: Follow the [:CONTAINS] and [:NEXT_DESTINATION] edges downstream.
3. Identify Terminal Nodes: Find the Customer nodes at the end of these paths.

The RAG Response: "The closure of the Suez Canal affects 50 of our Tier-1 orders. The most critical one is the Heart Valve shipment for Hamburg Hospital, currently 2 hops away from the blockage."

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3. Alternative Pathfinding (The Optimization)

If a path is blocked, the AI agent can run a Shortest Path query (with weighted edges) to find the next best route.

• Weights: Cost, Time, Risk.

Logical Reasoning: "I've found an alternative route via the Cape of Good Hope. It adds 10 days to the lead time but avoids the high-risk zone. Do you want me to update the flight plans for the perishable components?"

graph TD
    P1[Port A: BLOCKED] --- S1[Shipment 101]
    S1 --- Pr1[Product: Laptop]
    Pr1 --- C1[Cust: Apple]
    
    P1 -.->|Alternative| P2[Port B: Open]
    P2 --- S1
    
    style P1 fill:#f44336,color:#fff
    style P2 fill:#34A853,color:#fff

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4. Implementation: A "What-If" Analysis in Cypher

MATCH (disruption:Location {name: 'Suez'})<-[:LOCATED_AT]-(shipment)
MATCH (shipment)-[:TRANSPORTS]->(product)-[:ORDERED_BY]->(customer)
WHERE customer.priority = 'Critical'
RETURN customer.name, product.name, shipment.eta;

// This query identifies the most 'Critical' customers 
// currently delayed by a specific geographical point.

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5. Summary and Exercises

Logistics Graph RAG is the "Dashboard of Reality."

• Dependency Mapping reveals the hidden vulnerability of a product.
• Downstream Crawling predicts the impact before it happens.
• Dynamic Pathfinding provides the solution to the problem.
• Real-time Ingestion (from GPS/API) keeps the graph "Live."

Exercises

1. Dependency Task: Your product is a "Cupcake." List 3 factory-level dependencies that would be nodes in your graph. (e.g., Flour Mill, Sugar Refinery, Packaging Plant).
2. The "Just-in-Time" Risk: If every part has a "Lead Time" property, how would you write a query to find the "Thinnest" link—the part that if delayed by 1 day, delays the whole project?
3. Visualization: Draw a graph representing a "Hub and Spoke" delivery network. Mark the "Hub" node as failed. How many "Spokes" are affected?

In the final lesson of this course, we look at what's next: The Future of Graph RAG: Graph Neural Networks (GNNs).