randarium
Datasets

Warehouse Location Generator

Generate realistic warehouse bin location codes in zone-aisle-shelf-bin format (e.g., A-12-3-B). Useful for inventory management, warehouse simulations, and logistics testing.

Also known as: bin location · storage location · warehouse code

seeded · synthetic data

Presets

Output

No output yet — set your options and hit .
About this tool, tips & examples

What it does

The Warehouse Location Generator produces bin location codes in the standard zone-aisle-shelf-bin format (A-12-3-B) — the addressing scheme real warehouses use. Configure the layout (zones A–Z, aisles per zone, shelves per aisle) to match a facility’s shape and generate up to 10,000 codes per run, seeded for stable fixtures.

Common use cases

  • Inventory system testing — location columns for stock tables, putaway logic, and bin-lookup features (presets for small, medium, and large warehouses).
  • WMS demos — plausible slotting data for warehouse-management dashboards and pick-path displays.
  • Barcode label testing — location codes to render and scan in label pipelines (pair with the Random Barcode tool for item codes).
  • Supply-chain simulations — location dimensions for capacity and travel-time modeling.

Settings

  • Zones (A–Z) — 1 to 26 zones.
  • Aisles per zone / Shelves per aisle — the facility’s shape; the code space is the product of your choices.
  • How many — 1 to 10,000 codes, exportable as text, CSV, or JSON.
  • Seed — identical seed + layout = identical codes.

Privacy note

Codes are generated locally in your browser; nothing is uploaded. They describe no real facility — synthetic addresses for synthetic shelves.

FAQ

Can codes repeat in a batch? Draws are independent, so repeats are possible — like multiple picks from the same bin. Dedupe when your fixture needs distinct locations.

How do I match my real facility’s format? Set zones/aisles/shelves to your layout’s ranges — the generated codes then fall inside your real address space, which matters for validation testing.

What pairs well with this? Fake Logistics for the shipments moving through these bins, Warehouse Schema for the analytics tables, and Fake Product Dataset for what’s on the shelves.