Bay Area Delivery Optimization
Polyglot persistence architecture combining PostgreSQL analytics and Neo4j graph algorithms for last-mile delivery optimization.
The Problem
Last-Mile Logistics
Food delivery platforms need efficient routing and hub placement. The challenge was optimizing last-mile logistics across the Bay Area's complex BART transit network.
The Approach
Polyglot Graph Analytics
Built a polyglot persistence architecture: PostgreSQL for ETL and ridership analytics (12 months of data), Neo4j for graph modeling (100+ nodes, 2,400+ edges). Applied Dijkstra shortest path, Louvain community detection, and PageRank centrality algorithms.
Technologies & Methods
The Results
Optimal Hub Placement
Identified 9 optimal BART pickup locations and 11 community hubs using Dijkstra, Louvain, and PageRank. The graph-based approach captured transit network topology that relational-only SQL analysis cannot express.