A synthetic data generator for modeling end-to-end reverse logistics operations, including customer returns, multi-tier hub processing, and event-based item flows through a supply chain network for a fictional e-commerce platform selling electronics in NCR.
returns.csv
- Table for customer-initiated return cases before any logistics processing begins. Each row corresponds to a single return request generated from synthetic customer behavior driven by city demand, seasonality, and product-category preferences.
events.csv
- Table for records the full lifecycle of each returned item across the logistics network. It includes physical movement (arrival and departure from hubs) and system-controlled delays (dwell time, batching, office hours).
hubs.csv
- Table for the physical and logical nodes of the reverse logistics system. It includes pickup hubs, sorting centers, and the warehouse, each represented as a unique hub_id. Each hub acts as a processing node where events occur.
- Pickup Hubs - First consolidation point. City-level aggregation
- Sorting Hubs - Subregional processing center
- Warehouse - Final consolidation point
- Arrived at Pickup Hub
- Departed from Pickup Hub
- Arrived at Sorting Center
- Departed from Sorting Center
- Arrived at Warehouse (Terminal Event)